EWAS
As
DMP_As_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'As_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_smk')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 11440
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 361
# Adjusted, p<0.05: 18621
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.04115
# Number of DMRs identified: 1
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals)
y = pDatcordMetal$As_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.2060937
TestCDFs2(Z = Z, y = y, X = X)
# 0.4714538
DMP_As_cord[[3]] = NULL
# Sensitivity analysis including fish consumption
DMP_As_cord_fish = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'As_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'fish_d_f1', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_smk_fish')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 11440
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 340
# Adjusted, p<0.05: 16980
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.018171
# Number of identified DMR: 0
DMP_As_cord_fish[[3]] = NULL
No adjustment for fish consumption
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
12
|
9217389
|
9217859
|
0
|
470
|
0
|
0
|
9
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_smk/As_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_smk/As_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_smk/As_log2_manhattan_DMP_adj.png")
As, female
pDatcordMetal_F = pDatcordMetal[pDatcordMetal$female_d == 1,]
pDatcordMetal_F$race_child2 = as.factor(as.numeric(pDatcordMetal_F$race_child2))
DMP_As_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'As_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_F_smk')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 17949
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 169
# Adjusted, p<0.05: 15998
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.9470011
# Number of DMRs identified: 2
# Global DNAm
ComBat.Betas.Metals_F = ComBat.Betas.Metals[,colnames(ComBat.Betas.Metals) %in% rownames(pDatcordMetal_F)]
ComBat.Betas.Metals_F = ComBat.Betas.Metals_F[,match(rownames(pDatcordMetal_F), colnames(ComBat.Betas.Metals_F))]
Z = as.matrix(ComBat.Betas.Metals_F)
y = pDatcordMetal_F$As_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_F)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.2649051
TestCDFs2(Z = Z, y = y, X = X)
# 0.6430838
DMP_As_F_cord[[3]] = NULL
# Sensitivity analysis including fish consumption
DMP_As_F_cord_fish = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'As_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'fish_d_f1', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_F_smk_fish')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 17949
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 163
# Adjusted, p<0.05: 17835
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.001399
# Number of DMRs identified: 2
DMP_As_F_cord_fish[[3]] = NULL
No adjustment for fish consumption
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
3
|
186490655
|
186490915
|
0
|
260
|
0
|
1.2e-06
|
5
|
|
11
|
34460106
|
34460386
|
0
|
280
|
0
|
5.6e-06
|
7
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_F_smk/As_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_F_smk/As_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_F_smk/As_log2_manhattan_DMP_adj.png")
As, male
pDatcordMetal_M = pDatcordMetal[pDatcordMetal$female_d == 0,]
pDatcordMetal_M$race_child2 = as.factor(as.numeric(pDatcordMetal_M$race_child2))
DMP_As_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'As_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_M_smk')
# Unadjusted, N = 192
# Unadjusted, p<0.05: 12218
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 192
# Adjusted, p<0.05: 17778
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.012338
# Number of DMRs identified: 6
# Global DNAm
ComBat.Betas.Metals_M = ComBat.Betas.Metals[,colnames(ComBat.Betas.Metals) %in% rownames(pDatcordMetal_M)]
ComBat.Betas.Metals_M = ComBat.Betas.Metals_M[,match(rownames(pDatcordMetal_M), colnames(ComBat.Betas.Metals_M))]
Z = as.matrix(ComBat.Betas.Metals_M)
y = pDatcordMetal_M$As_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_M)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.5010154
TestCDFs2(Z = Z, y = y, X = X)
# 0.4794129
DMP_As_M_cord[[3]] = NULL
# Sensitivity analysis including fish consumption
DMP_As_M_cord_fish = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'As_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'fish_d_f1', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_M_smk_fish')
# Unadjusted, N = 192
# Unadjusted, p<0.05: 12218
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 177
# Adjusted, p<0.05: 17523
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.045777
# Number of identified DMR: 0
DMP_As_M_cord_fish[[3]] = NULL
No adjustment for fish consumption
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
12
|
9217389
|
9217859
|
0.0000000
|
470
|
0.0000000
|
0.0000000
|
9
|
|
20
|
3051953
|
3052345
|
0.0000000
|
392
|
0.0000000
|
0.0000001
|
9
|
|
11
|
18433499
|
18433683
|
0.0000000
|
184
|
0.0000001
|
0.0000834
|
4
|
|
11
|
1036676
|
1036766
|
0.0000184
|
90
|
0.0000228
|
0.0775082
|
3
|
|
11
|
2890628
|
2890670
|
0.0000190
|
42
|
0.0000228
|
0.1632398
|
6
|
|
6
|
32063990
|
32064032
|
0.0062251
|
42
|
0.0062251
|
1.0000000
|
2
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_M_smk/As_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_M_smk/As_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/As_M_smk/As_log2_manhattan_DMP_adj.png")
Ba
DMP_Ba_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Ba_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_smk')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 21408
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 361
# Adjusted, p<0.05: 18979
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.005839
# Number of identified DMR: 0
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals)
y = pDatcordMetal$Ba_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 1
TestCDFs2(Z = Z, y = y, X = X)
# 0.9642374
DMP_Ba_cord[[3]] = NULL
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_smk/Ba_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_smk/Ba_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_smk/Ba_log2_manhattan_DMP_adj.png")
Ba, female
DMP_Ba_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Ba_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_F_smk')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 16994
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 169
# Adjusted, p<0.05: 13447
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.7988493
# Number of DMRs identified: 2
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_F)
y = pDatcordMetal_F$Ba_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_F)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.8719371
TestCDFs2(Z = Z, y = y, X = X)
# 0.9047666
DMP_Ba_F_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
10
|
135051255
|
135051581
|
0
|
326
|
0
|
1.1e-06
|
7
|
|
8
|
144635259
|
144635610
|
0
|
351
|
0
|
6.8e-06
|
9
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_F_smk/Ba_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_F_smk/Ba_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_F_smk/Ba_log2_manhattan_DMP_adj.png")
Ba, male
DMP_Ba_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Ba_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_M_smk')
# Unadjusted, N = 192
# Unadjusted, p<0.05: 16173
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 192
# Adjusted, p<0.05: 14253
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.8647773
# Number of DMRs identified: 2
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_M)
y = pDatcordMetal_M$Ba_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_M)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.6918766
TestCDFs2(Z = Z, y = y, X = X)
# 0.8282238
DMP_Ba_M_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
4
|
169239618
|
169240010
|
0
|
392
|
0
|
0e+00
|
7
|
|
10
|
135278716
|
135279147
|
0
|
431
|
0
|
2e-07
|
5
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_M_smk/Ba_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_M_smk/Ba_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Ba_M_smk/Ba_log2_manhattan_DMP_adj.png")
Cd
DMP_Cd_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Cd_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_smk')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 13284
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 361
# Adjusted, p<0.05: 16155
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.9008795
# Number of DMRs identified: 5
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals)
y = pDatcordMetal$Cd_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.9505146
TestCDFs2(Z = Z, y = y, X = X)
# 0.9287107
DMP_Cd_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
3
|
156323951
|
156324118
|
0.0000000
|
167
|
0.0000000
|
0.0000021
|
3
|
|
13
|
110319561
|
110319607
|
0.0000000
|
46
|
0.0000000
|
0.0000112
|
3
|
|
17
|
46685291
|
46685448
|
0.0000000
|
157
|
0.0000000
|
0.0000200
|
5
|
|
2
|
200468625
|
200468832
|
0.0000001
|
207
|
0.0000001
|
0.0001135
|
3
|
|
6
|
30039141
|
30039175
|
0.0079818
|
34
|
0.0079818
|
1.0000000
|
3
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_smk/Cd_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_smk/Cd_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_smk/Cd_log2_manhattan_DMP_adj.png")
Cd, female
DMP_Cd_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Cd_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_F_smk')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 19177
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 169
# Adjusted, p<0.05: 17515
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.9484605
# Number of DMRs identified: 2
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_F)
y = pDatcordMetal_F$Cd_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_F)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.6774836
TestCDFs2(Z = Z, y = y, X = X)
# 0.7989639
DMP_Cd_F_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
7
|
27225810
|
27225897
|
3e-07
|
87
|
5e-07
|
0.0011375
|
4
|
|
2
|
200468625
|
200468728
|
5e-06
|
103
|
5e-06
|
0.0188741
|
2
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_F_smk/Cd_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_F_smk/Cd_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_F_smk/Cd_log2_manhattan_DMP_adj.png")
Cd, male
DMP_Cd_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Cd_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_M_smk')
# Unadjusted, N = 192
# Unadjusted, p<0.05: 8842
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 192
# Adjusted, p<0.05: 16112
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.9725517
# Number of DMRs identified: 4
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_M)
y = pDatcordMetal_M$Cd_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_M)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 1
TestCDFs2(Z = Z, y = y, X = X)
# 0.4183672
DMP_Cd_M_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
19
|
37742738
|
37742956
|
0.0e+00
|
218
|
0.0e+00
|
0.0000000
|
4
|
|
20
|
61583909
|
61584159
|
0.0e+00
|
250
|
1.0e-07
|
0.0000481
|
7
|
|
6
|
26018002
|
26018185
|
0.0e+00
|
183
|
1.0e-07
|
0.0000876
|
6
|
|
6
|
28446839
|
28447087
|
9.6e-05
|
248
|
9.6e-05
|
0.1416376
|
2
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_M_smk/Cd_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_M_smk/Cd_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cd_M_smk/Cd_log2_manhattan_DMP_adj.png")
Cr
DMP_Cr_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Cr_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_smk')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 19469
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 361
# Adjusted, p<0.05: 20800
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.012833
# Number of DMRs identified: 4
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals)
y = pDatcordMetal$Cr_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.6865602
TestCDFs2(Z = Z, y = y, X = X)
# 0.824518
DMP_Cr_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
8
|
13373032
|
13373141
|
0.0000000
|
109
|
0.0000000
|
0.0000010
|
3
|
|
6
|
33245700
|
33246008
|
0.0000000
|
308
|
0.0000000
|
0.0000041
|
13
|
|
10
|
114713023
|
114713187
|
0.0000000
|
164
|
0.0000001
|
0.0001122
|
3
|
|
17
|
46641862
|
46642011
|
0.0001097
|
149
|
0.0001097
|
0.2519895
|
2
|
No adjustment for fish consumption
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_smk/Cr_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_smk/Cr_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_smk/Cr_log2_manhattan_DMP_adj.png")
Cr, female
DMP_Cr_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Cr_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_F_smk')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 15600
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 169
# Adjusted, p<0.05: 14094
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.8406537
# Number of DMRs identified: 2
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_F)
y = pDatcordMetal_F$Cr_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_F)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 1
TestCDFs2(Z = Z, y = y, X = X)
# 0.9618538
DMP_Cr_F_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
8
|
13373032
|
13373141
|
0
|
109
|
0
|
0.00e+00
|
3
|
|
7
|
81240444
|
81240667
|
0
|
223
|
0
|
2.98e-05
|
4
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_F_smk/Cr_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_F_smk/Cr_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_F_smk/Cr_log2_manhattan_DMP_adj.png")
Cr, male
DMP_Cr_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Cr_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_M_smk')
# Unadjusted, N = 192
# Unadjusted, p<0.05: 13268
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 192
# Adjusted, p<0.05: 16129
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.91629
# Number of identified DMR: 0
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_M)
y = pDatcordMetal_M$Cr_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_M)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.5270954
TestCDFs2(Z = Z, y = y, X = X)
# 0.7370205
DMP_Cr_M_cord[[3]] = NULL
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_M_smk/Cr_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_M_smk/Cr_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cr_M_smk/Cr_log2_manhattan_DMP_adj.png")
Cs
DMP_Cs_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Cs_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_smk')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 28868
# Unadjusted, FDR<0.05: 5
# Unadjusted, pBonf<0.05: 3
# Adjusted, N = 361
# Adjusted, p<0.05: 19656
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.023771
# Number of DMRs identified: 19
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals)
y = pDatcordMetal$Cs_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.4773269
TestCDFs2(Z = Z, y = y, X = X)
# 0.4819991
DMP_Cs_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
4
|
174421376
|
174422626
|
0.0000000
|
1250
|
0.0000000
|
0.0000000
|
7
|
|
6
|
33280051
|
33280478
|
0.0000000
|
427
|
0.0000000
|
0.0000000
|
14
|
|
6
|
28601268
|
28601519
|
0.0000000
|
251
|
0.0000000
|
0.0000001
|
11
|
|
6
|
30881315
|
30881842
|
0.0000000
|
527
|
0.0000000
|
0.0000001
|
21
|
|
20
|
57427273
|
57427762
|
0.0000000
|
489
|
0.0000000
|
0.0000002
|
16
|
|
17
|
17603530
|
17603837
|
0.0000000
|
307
|
0.0000000
|
0.0000003
|
4
|
|
6
|
32847440
|
32847845
|
0.0000000
|
405
|
0.0000000
|
0.0000005
|
17
|
|
1
|
75590911
|
75591029
|
0.0000000
|
118
|
0.0000000
|
0.0000230
|
3
|
|
12
|
44152508
|
44152940
|
0.0000000
|
432
|
0.0000000
|
0.0000139
|
11
|
|
12
|
1025528
|
1025755
|
0.0000000
|
227
|
0.0000001
|
0.0000524
|
3
|
|
12
|
54763210
|
54763433
|
0.0000000
|
223
|
0.0000001
|
0.0000748
|
3
|
|
15
|
69325270
|
69325560
|
0.0000001
|
290
|
0.0000001
|
0.0000909
|
5
|
|
8
|
43131259
|
43131656
|
0.0000001
|
397
|
0.0000001
|
0.0000717
|
5
|
|
19
|
10736005
|
10736117
|
0.0000001
|
112
|
0.0000001
|
0.0002945
|
5
|
|
3
|
141087186
|
141087363
|
0.0000001
|
177
|
0.0000001
|
0.0002012
|
5
|
|
5
|
78985424
|
78985592
|
0.0000001
|
168
|
0.0000001
|
0.0002371
|
9
|
|
17
|
46388389
|
46388465
|
0.0000003
|
76
|
0.0000003
|
0.0015858
|
3
|
|
8
|
143859708
|
143859895
|
0.0000034
|
187
|
0.0000036
|
0.0072132
|
5
|
|
6
|
31651019
|
31651029
|
0.0060013
|
10
|
0.0060013
|
1.0000000
|
2
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_smk/Cs_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_smk/Cs_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_smk/Cs_log2_manhattan_DMP_adj.png")
Cs, female
DMP_Cs_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Cs_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_F_smk')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 14228
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 169
# Adjusted, p<0.05: 11215
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.7833446
# Number of DMRs identified: 3
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_F)
y = pDatcordMetal_F$Cs_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_F)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.6525172
TestCDFs2(Z = Z, y = y, X = X)
# 0.9363569
DMP_Cs_F_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
12
|
44152508
|
44152940
|
0
|
432
|
0
|
0.00e+00
|
11
|
|
6
|
117923794
|
117924070
|
0
|
276
|
0
|
1.22e-05
|
8
|
|
1
|
26233331
|
26233623
|
0
|
292
|
0
|
4.13e-05
|
10
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_F_smk/Cs_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_F_smk/Cs_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_F_smk/Cs_log2_manhattan_DMP_adj.png")
Cs, male
DMP_Cs_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Cs_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_M_smk')
Unadjusted, N = 192
Unadjusted, p<0.05: 23725
Unadjusted, FDR<0.05: 0
Unadjusted, pBonf<0.05: 0
Adjusted, N = 192
Adjusted, p<0.05: 20888
Adjusted, FDR<0.05: 0
Adjusted, pBonf<0.05: 0
Adjusted, lambda: 1.090349
Number of DMRs identified: 14
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_M)
y = pDatcordMetal_M$Cs_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_M)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.9909583
TestCDFs2(Z = Z, y = y, X = X)
# 0.5722894
DMP_Cs_M_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
6
|
31650734
|
31651362
|
0e+00
|
628
|
0e+00
|
0.0000000
|
21
|
|
8
|
43131259
|
43132507
|
0e+00
|
1248
|
0e+00
|
0.0000000
|
8
|
|
15
|
69325270
|
69325560
|
0e+00
|
290
|
0e+00
|
0.0000000
|
5
|
|
17
|
17603530
|
17604146
|
0e+00
|
616
|
0e+00
|
0.0000000
|
5
|
|
12
|
108634146
|
108634275
|
0e+00
|
129
|
0e+00
|
0.0000021
|
3
|
|
6
|
28601268
|
28601519
|
0e+00
|
251
|
0e+00
|
0.0000033
|
11
|
|
3
|
141087186
|
141087363
|
0e+00
|
177
|
0e+00
|
0.0000070
|
5
|
|
10
|
134150488
|
134150760
|
0e+00
|
272
|
1e-07
|
0.0000443
|
7
|
|
6
|
30881463
|
30881766
|
1e-07
|
303
|
1e-07
|
0.0001385
|
15
|
|
19
|
51774376
|
51774666
|
1e-07
|
290
|
1e-07
|
0.0001576
|
4
|
|
14
|
21148813
|
21148957
|
1e-07
|
144
|
1e-07
|
0.0003211
|
2
|
|
6
|
28446839
|
28447115
|
1e-07
|
276
|
2e-07
|
0.0002129
|
4
|
|
4
|
187422004
|
187422119
|
2e-07
|
115
|
2e-07
|
0.0006659
|
5
|
|
13
|
23309929
|
23310203
|
4e-07
|
274
|
4e-07
|
0.0005853
|
3
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_M_smk/Cs_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_M_smk/Cs_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cs_M_smk/Cs_log2_manhattan_DMP_adj.png")
Cu
DMP_Cu_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Cu_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_smk')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 31830
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 361
# Adjusted, p<0.05: 57431
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.843163
# Number of DMRs identified: 4
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals)
y = pDatcordMetal$Cu_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.4060445
TestCDFs2(Z = Z, y = y, X = X)
# 0.0567817
DMP_Cu_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
4
|
174421376
|
174422626
|
0.0000000
|
1250
|
0.0000000
|
0.0000000
|
7
|
|
6
|
33280051
|
33280478
|
0.0000000
|
427
|
0.0000000
|
0.0000000
|
14
|
|
6
|
28601268
|
28601519
|
0.0000000
|
251
|
0.0000000
|
0.0000001
|
11
|
|
6
|
30881315
|
30881842
|
0.0000000
|
527
|
0.0000000
|
0.0000001
|
21
|
|
20
|
57427273
|
57427762
|
0.0000000
|
489
|
0.0000000
|
0.0000002
|
16
|
|
17
|
17603530
|
17603837
|
0.0000000
|
307
|
0.0000000
|
0.0000003
|
4
|
|
6
|
32847440
|
32847845
|
0.0000000
|
405
|
0.0000000
|
0.0000005
|
17
|
|
1
|
75590911
|
75591029
|
0.0000000
|
118
|
0.0000000
|
0.0000230
|
3
|
|
12
|
44152508
|
44152940
|
0.0000000
|
432
|
0.0000000
|
0.0000139
|
11
|
|
12
|
1025528
|
1025755
|
0.0000000
|
227
|
0.0000001
|
0.0000524
|
3
|
|
12
|
54763210
|
54763433
|
0.0000000
|
223
|
0.0000001
|
0.0000748
|
3
|
|
15
|
69325270
|
69325560
|
0.0000001
|
290
|
0.0000001
|
0.0000909
|
5
|
|
8
|
43131259
|
43131656
|
0.0000001
|
397
|
0.0000001
|
0.0000717
|
5
|
|
19
|
10736005
|
10736117
|
0.0000001
|
112
|
0.0000001
|
0.0002945
|
5
|
|
3
|
141087186
|
141087363
|
0.0000001
|
177
|
0.0000001
|
0.0002012
|
5
|
|
5
|
78985424
|
78985592
|
0.0000001
|
168
|
0.0000001
|
0.0002371
|
9
|
|
17
|
46388389
|
46388465
|
0.0000003
|
76
|
0.0000003
|
0.0015858
|
3
|
|
8
|
143859708
|
143859895
|
0.0000034
|
187
|
0.0000036
|
0.0072132
|
5
|
|
6
|
31651019
|
31651029
|
0.0060013
|
10
|
0.0060013
|
1.0000000
|
2
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_smk/Cu_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_smk/Cu_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_smk/Cu_log2_manhattan_DMP_adj.png")
Cu, female
DMP_Cu_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Cu_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_F_smk')
# # Unadjusted, N = 169
# Unadjusted, p<0.05: 34435
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 169
# Adjusted, p<0.05: 17151
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.051202
# Number of DMRs identified: 2
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_F)
y = pDatcordMetal_F$Cu_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_F)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.2201764
TestCDFs2(Z = Z, y = y, X = X)
# 0.2115454
DMP_Cu_F_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
20
|
57427442
|
57427942
|
0.0000000
|
500
|
0.0000000
|
0.0000001
|
16
|
|
11
|
368613
|
368847
|
0.0001141
|
234
|
0.0001141
|
0.1749727
|
5
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_F_smk/Cu_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_F_smk/Cu_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_F_smk/Cu_log2_manhattan_DMP_adj.png")
Cu, male
DMP_Cu_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Cu_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_M_smk')
# Unadjusted, N = 192
# Unadjusted, p<0.05: 10164
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 192
# Adjusted, p<0.05: 57571
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.920529
# Number of DMRs identified: 7
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_M)
y = pDatcordMetal_M$Cu_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_M)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.8831614
TestCDFs2(Z = Z, y = y, X = X)
# 0.2219984
DMP_Cu_M_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
5
|
83016999
|
83017184
|
0.0000000
|
185
|
0.0000000
|
0.0000003
|
4
|
|
3
|
46759437
|
46759698
|
0.0000000
|
261
|
0.0000000
|
0.0000118
|
7
|
|
1
|
108023248
|
108023482
|
0.0000000
|
234
|
0.0000001
|
0.0000635
|
5
|
|
11
|
1283874
|
1283970
|
0.0000000
|
96
|
0.0000001
|
0.0001836
|
3
|
|
6
|
32847761
|
32847845
|
0.0000043
|
84
|
0.0000053
|
0.0201783
|
7
|
|
12
|
54673866
|
54674009
|
0.0000045
|
143
|
0.0000053
|
0.0123676
|
4
|
|
3
|
42977888
|
42977896
|
0.0009588
|
8
|
0.0009588
|
1.0000000
|
2
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_M_smk/Cu_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_M_smk/Cu_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Cu_M_smk/Cu_log2_manhattan_DMP_adj.png")
Hg
DMP_Hg_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Hg_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_smk')
# Unadjusted, N = 358
# Unadjusted, p<0.05: 38119
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 358
# Adjusted, p<0.05: 13574
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.7969179
# Number of DMRs identified: 2
# Global DNAm
pDatcordMetal_Hg = pDatcordMetal[!is.na(pDatcordMetal$Hg_log2),]
dim(pDatcordMetal_Hg)
# 358 165
ComBat.Betas.Metals_Hg = ComBat.Betas.Metals[,colnames(ComBat.Betas.Metals) %in% rownames(pDatcordMetal_Hg)]
ComBat.Betas.Metals_Hg = ComBat.Betas.Metals_Hg[,match(rownames(pDatcordMetal_Hg), colnames(ComBat.Betas.Metals_Hg))]
Z = as.matrix(ComBat.Betas.Metals_Hg)
y = pDatcordMetal_Hg$Hg_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_Hg)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 1
TestCDFs2(Z = Z, y = y, X = X)
# 0.8498853
DMP_Hg_cord[[3]] = NULL
# Sensitivity analysis including fish consumption
DMP_Hg_cord_fish = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Hg_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'fish_d_f1', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_smk_fish')
# Unadjusted, N = 358
# Unadjusted, p<0.05: 38119
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 337
# Adjusted, p<0.05: 12500
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.789449
# Number of DMRs identified: 1
DMP_Hg_cord_fish[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
8
|
143859668
|
143859990
|
0
|
322
|
0
|
0.00e+00
|
7
|
|
6
|
30039373
|
30039548
|
0
|
175
|
0
|
2.67e-05
|
12
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_smk/Hg_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_smk/Hg_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_smk/Hg_log2_manhattan_DMP_adj.png")
Hg, female
DMP_Hg_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Hg_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_F_smk')
# Unadjusted, N = 167
# Unadjusted, p<0.05: 11528
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 167
# Adjusted, p<0.05: 10058
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.7103341
# Number of identified DMR: 0
# Global DNAm
pDatcordMetal_HgF = pDatcordMetal_Hg[pDatcordMetal_Hg$female_d == 1,]
dim(pDatcordMetal_HgF)
# 167 165
ComBat.Betas.Metals_HgF = ComBat.Betas.Metals[,colnames(ComBat.Betas.Metals) %in% rownames(pDatcordMetal_HgF)]
ComBat.Betas.Metals_HgF = ComBat.Betas.Metals_HgF[,match(rownames(pDatcordMetal_HgF), colnames(ComBat.Betas.Metals_HgF))]
Z = as.matrix(ComBat.Betas.Metals_HgF)
y = pDatcordMetal_HgF$Hg_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_HgF)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 1
TestCDFs2(Z = Z, y = y, X = X)
# 0.9751191
DMP_Hg_F_cord[[3]] = NULL
# Sensitivity analysis including fish consumption
DMP_Hg_F_cord_fish = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Hg_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'fish_d_f1', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_F_smk_fish')
# Unadjusted, N = 167
# Unadjusted, p<0.05: 11528
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 161
# Adjusted, p<0.05: 9299
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.7007602
# Number of identified DMR: 0
DMP_Hg_F_cord_fish[[3]] = NULL
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_F_smk/Hg_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_F_smk/Hg_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_F_smk/Hg_log2_manhattan_DMP_adj.png")
Hg, male
DMP_Hg_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Hg_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_M_smk')
# Unadjusted, N = 191
# Unadjusted, p<0.05: 32177
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 191
# Adjusted, p<0.05: 12443
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.7917212
# Number of DMRs identified: 3
# Global DNAm
pDatcordMetal_HgM = pDatcordMetal_Hg[pDatcordMetal_Hg$female_d == 0,]
dim(pDatcordMetal_HgM)
# 191 164
ComBat.Betas.Metals_HgM = ComBat.Betas.Metals[,colnames(ComBat.Betas.Metals) %in% rownames(pDatcordMetal_HgM)]
ComBat.Betas.Metals_HgM = ComBat.Betas.Metals_HgM[,match(rownames(pDatcordMetal_HgM), colnames(ComBat.Betas.Metals_HgM))]
Z = as.matrix(ComBat.Betas.Metals_HgM)
y = pDatcordMetal_HgM$Hg_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_HgM)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 1
TestCDFs2(Z = Z, y = y, X = X)
# 0.8541436
DMP_Hg_M_cord[[3]] = NULL
# Sensitivity analysis including fish consumption
DMP_Hg_M_cord_fish = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Hg_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'fish_d_f1', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_M_smk_fish')
# Unadjusted, N = 191
# Unadjusted, p<0.05: 32177
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 176
# Adjusted, p<0.05: 13414
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.8575889
# Number of DMRs identified: 2
DMP_Hg_M_cord_fish[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
8
|
143859668
|
143859990
|
0
|
322
|
0
|
0e+00
|
7
|
|
6
|
30039141
|
30039548
|
0
|
407
|
0
|
0e+00
|
15
|
|
6
|
31650785
|
31651291
|
0
|
506
|
0
|
1e-07
|
18
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_M_smk/Hg_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_M_smk/Hg_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Hg_M_smk/Hg_log2_manhattan_DMP_adj.png")
Mg
DMP_Mg_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Mg_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_smk')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 20828
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 361
# Adjusted, p<0.05: 19872
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.06817
# Number of DMRs identified: 5
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals)
y = pDatcordMetal$Mg_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.4836713
TestCDFs2(Z = Z, y = y, X = X)
# 0.3595287
DMP_Mg_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
20
|
57427169
|
57427973
|
0.0e+00
|
804
|
0.0e+00
|
0.0000000
|
24
|
|
6
|
30039174
|
30039548
|
0.0e+00
|
374
|
0.0e+00
|
0.0000000
|
13
|
|
1
|
2980037
|
2980399
|
0.0e+00
|
362
|
0.0e+00
|
0.0000026
|
4
|
|
6
|
32063990
|
32064258
|
0.0e+00
|
268
|
1.0e-07
|
0.0000691
|
12
|
|
11
|
368564
|
368712
|
8.7e-06
|
148
|
8.7e-06
|
0.0229495
|
7
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_smk/Mg_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_smk/Mg_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_smk/Mg_log2_manhattan_DMP_adj.png")
Mg, female
DMP_Mg_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Mg_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_F_smk')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 21465
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 169
# Adjusted, p<0.05: 15195
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.8709494
# Number of DMRs identified: 4
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_F)
y = pDatcordMetal_F$Mg_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_F)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.4362102
TestCDFs2(Z = Z, y = y, X = X)
# 0.5301462
DMP_Mg_F_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
17
|
48912264
|
48912621
|
0.00e+00
|
357
|
0.00e+00
|
0.0000001
|
9
|
|
20
|
57427442
|
57427762
|
0.00e+00
|
320
|
0.00e+00
|
0.0000136
|
13
|
|
14
|
105944941
|
105945022
|
1.90e-06
|
81
|
2.50e-06
|
0.0091077
|
2
|
|
19
|
45976119
|
45976195
|
4.37e-05
|
76
|
4.37e-05
|
0.2027450
|
2
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_F_smk/Mg_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_F_smk/Mg_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_F_smk/Mg_log2_manhattan_DMP_adj.png")
Mg, male
DMP_Mg_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Mg_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_M_smk')
# Unadjusted, N = 192
# Unadjusted, p<0.05: 38543
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 192
# Adjusted, p<0.05: 40269
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.596383
# Number of DMRs identified: 1
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_M)
y = pDatcordMetal_M$Mg_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_M)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.6709343
TestCDFs2(Z = Z, y = y, X = X)
# 0.3772599
DMP_Mg_M_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
19
|
57742111
|
57742423
|
0
|
312
|
0
|
3e-07
|
7
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_M_smk/Mg_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_M_smk/Mg_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mg_M_smk/Mg_log2_manhattan_DMP_adj.png")
Mn
DMP_Mn_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Mn_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_smk')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 9732
# Unadjusted, FDR<0.05: 1
# Unadjusted, pBonf<0.05: 1
# Adjusted, N = 361
# Adjusted, p<0.05: 10272
# Adjusted, FDR<0.05: 1
# Adjusted, pBonf<0.05: 1
# Adjusted, lambda: 0.7354948
# Number of DMRs identified: 2
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals)
y = pDatcordMetal$Mn_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 1
TestCDFs2(Z = Z, y = y, X = X)
# 0.9816769
DMP_Mn_cord[[3]] = NULL
# limma on Beta-values
DMP_Mn_cord_Beta = run_EWAS(DNAm = ComBat.Betas.Metals, pheno = pDatcordMetal, var = 'Mn_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_smk_beta')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 9703
# Unadjusted, FDR<0.05: 77
# Unadjusted, pBonf<0.05: 27
# Adjusted, N = 361
# Adjusted, p<0.05: 10999
# Adjusted, FDR<0.05: 79
# Adjusted, pBonf<0.05: 30
# Adjusted, lambda: 0.7346154
# Number of DMRs identified: 14
DMP_Mn_cord_Beta[[3]][DMP_Mn_cord_Beta[[3]]$cpg == 'cg02042823',c(2:4)]*100
# logFC CI.L CI.R
# cg02042823 2.649407 2.067173 3.231641
rm(DMP_Mn_cord_Beta)
# Sex x Mn interactions
pDatcordMetal$cg02042823 = ComBat.Mvalues.Metals[rownames(ComBat.Mvalues.Metals) == 'cg02042823',]
pDatcordMetal$cg00954161 = ComBat.Mvalues.Metals[rownames(ComBat.Mvalues.Metals) == 'cg00954161',]
pDatcordMetal$cg11161853 = ComBat.Mvalues.Metals[rownames(ComBat.Mvalues.Metals) == 'cg11161853',]
pDatcordMetal$cg23903787 = ComBat.Mvalues.Metals[rownames(ComBat.Mvalues.Metals) == 'cg23903787',]
pDatcordMetal$cg19908812 = ComBat.Mvalues.Metals[rownames(ComBat.Mvalues.Metals) == 'cg19908812',]
pDatcordMetal$cg26462130 = ComBat.Mvalues.Metals[rownames(ComBat.Mvalues.Metals) == 'cg26462130',]
pDatcordMetal$cg08904630 = ComBat.Mvalues.Metals[rownames(ComBat.Mvalues.Metals) == 'cg08904630',]
pDatcordMetal$cg22799518 = ComBat.Mvalues.Metals[rownames(ComBat.Mvalues.Metals) == 'cg22799518',]
pDatcordMetal$cg01744822 = ComBat.Mvalues.Metals[rownames(ComBat.Mvalues.Metals) == 'cg01744822',]
pDatcordMetal$cg15712310 = ComBat.Mvalues.Metals[rownames(ComBat.Mvalues.Metals) == 'cg15712310',]
pDatcordMetal$cg03763518 = ComBat.Mvalues.Metals[rownames(ComBat.Mvalues.Metals) == 'cg03763518',]
summary(lm(cg02042823 ~ Mn_log2*female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal))
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) -6.229288 4.752119 -1.311 0.19080
# Mn_log2 0.507448 0.074999 6.766 5.85e-11 ***
# female_d1 1.066988 0.536069 1.990 0.04735 *
# race_child22 0.232898 0.170639 1.365 0.17321
# race_child23 -0.149198 0.220554 -0.676 0.49921
# race_child24 -0.094920 0.332073 -0.286 0.77518
# race_child25 -0.113221 0.160587 -0.705 0.48127
# gestage_wks_deliv_d 0.005978 0.034226 0.175 0.86146
# age_mom_enroll_d 0.009590 0.010823 0.886 0.37619
# bmi_mom_prepreg_d 0.010942 0.009895 1.106 0.26958
# coll_grad1 0.002723 0.124350 0.022 0.98254
# nullip1 -0.047540 0.104451 -0.455 0.64930
# gt70k1 0.048305 0.109705 0.440 0.65999
# smk_preg21 0.026667 0.123308 0.216 0.82891
# smk_preg22 0.080889 0.163894 0.494 0.62195
# Bcell_GS_cb 9.987107 4.084519 2.445 0.01499 *
# CD4T_GS_cb 8.558499 4.445071 1.925 0.05502 .
# CD8T_GS_cb 10.715863 4.059726 2.640 0.00869 **
# Gran_GS_cb 8.736424 4.189107 2.086 0.03777 *
# Mono_GS_cb 5.361756 4.219680 1.271 0.20473
# NK_GS_cb 11.109924 4.827756 2.301 0.02198 *
# nRBC_GS_cb 5.621310 3.864676 1.455 0.14673
# Mn_log2:female_d1 -0.249108 0.132056 -1.886 0.06010 .
summary(lm(cg00954161 ~ Mn_log2*female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal))
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) -8.552121 3.229710 -2.648 0.008478 **
# Mn_log2 0.062337 0.050972 1.223 0.222198
# female_d1 -1.417436 0.364332 -3.891 0.000120 ***
# race_child22 0.125829 0.115972 1.085 0.278697
# race_child23 0.010367 0.149896 0.069 0.944900
# race_child24 0.073370 0.225689 0.325 0.745312
# race_child25 -0.032562 0.109141 -0.298 0.765621
# gestage_wks_deliv_d 0.023038 0.023261 0.990 0.322676
# age_mom_enroll_d -0.001793 0.007355 -0.244 0.807521
# bmi_mom_prepreg_d 0.009305 0.006725 1.384 0.167366
# coll_grad1 -0.016253 0.084512 -0.192 0.847615
# nullip1 0.002808 0.070989 0.040 0.968471
# gt70k1 -0.093024 0.074559 -1.248 0.213022
# smk_preg21 0.039727 0.083805 0.474 0.635780
# smk_preg22 0.058622 0.111388 0.526 0.599034
# Bcell_GS_cb 11.558065 2.775986 4.164 3.98e-05 ***
# CD4T_GS_cb 13.987591 3.021030 4.630 5.22e-06 ***
# CD8T_GS_cb 8.316463 2.759135 3.014 0.002772 **
# Gran_GS_cb 12.479572 2.847067 4.383 1.56e-05 ***
# Mono_GS_cb 12.164113 2.867846 4.242 2.87e-05 ***
# NK_GS_cb 11.697179 3.281116 3.565 0.000416 ***
# nRBC_GS_cb 11.784569 2.626572 4.487 9.93e-06 ***
# Mn_log2:female_d1 0.361109 0.089750 4.024 7.08e-05 ***
summary(lm(cg11161853 ~ Mn_log2*female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal))
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) -5.2369391 1.0609188 -4.936 1.25e-06 ***
# Mn_log2 0.0174724 0.0167438 1.044 0.297
# female_d1 0.6402879 0.1196783 5.350 1.62e-07 ***
# race_child22 -0.0271573 0.0380954 -0.713 0.476
# race_child23 -0.0481153 0.0492390 -0.977 0.329
# race_child24 0.0538946 0.0741359 0.727 0.468
# race_child25 -0.0247498 0.0358514 -0.690 0.490
# gestage_wks_deliv_d -0.0035721 0.0076410 -0.467 0.640
# age_mom_enroll_d -0.0017320 0.0024162 -0.717 0.474
# bmi_mom_prepreg_d 0.0001844 0.0022091 0.083 0.934
# coll_grad1 0.0243383 0.0277613 0.877 0.381
# nullip1 0.0143435 0.0233189 0.615 0.539
# gt70k1 -0.0128355 0.0244918 -0.524 0.601
# smk_preg21 -0.0186029 0.0275288 -0.676 0.500
# smk_preg22 0.0026574 0.0365896 0.073 0.942
# Bcell_GS_cb -0.0556373 0.9118760 -0.061 0.951
# CD4T_GS_cb -0.1114615 0.9923699 -0.112 0.911
# CD8T_GS_cb -0.2022964 0.9063409 -0.223 0.824
# Gran_GS_cb 0.0391510 0.9352254 0.042 0.967
# Mono_GS_cb 0.0490554 0.9420511 0.052 0.959
# NK_GS_cb -0.0780079 1.0778049 -0.072 0.942
# nRBC_GS_cb 0.0982060 0.8627957 0.114 0.909
# Mn_log2:female_d1 -0.1468865 0.0294816 -4.982 1.00e-06 ***
summary(lm(cg23903787 ~ Mn_log2*female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal))
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) -4.686794 3.331625 -1.407 0.160418
# Mn_log2 -0.025216 0.052581 -0.480 0.631841
# female_d1 -1.481459 0.375828 -3.942 9.83e-05 ***
# race_child22 0.140949 0.119632 1.178 0.239550
# race_child23 -0.217690 0.154626 -1.408 0.160095
# race_child24 0.164864 0.232810 0.708 0.479342
# race_child25 0.133239 0.112585 1.183 0.237460
# gestage_wks_deliv_d 0.077484 0.023995 3.229 0.001363 **
# age_mom_enroll_d 0.004198 0.007587 0.553 0.580402
# bmi_mom_prepreg_d 0.003832 0.006937 0.552 0.581009
# coll_grad1 0.005777 0.087179 0.066 0.947207
# nullip1 0.028402 0.073229 0.388 0.698366
# gt70k1 -0.101465 0.076912 -1.319 0.187983
# smk_preg21 -0.087276 0.086449 -1.010 0.313429
# smk_preg22 -0.078713 0.114903 -0.685 0.493787
# Bcell_GS_cb 4.483483 2.863583 1.566 0.118357
# CD4T_GS_cb 4.639408 3.116360 1.489 0.137492
# CD8T_GS_cb 4.199998 2.846201 1.476 0.140969
# Gran_GS_cb 4.349368 2.936908 1.481 0.139556
# Mono_GS_cb 2.760638 2.958342 0.933 0.351398
# NK_GS_cb 4.791331 3.384653 1.416 0.157812
# nRBC_GS_cb 4.223987 2.709455 1.559 0.119937
# Mn_log2:female_d1 0.359894 0.092582 3.887 0.000122 ***
summary(lm(cg19908812 ~ Mn_log2*female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal))
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) -2.152399 1.396858 -1.541 0.12428
# Mn_log2 -0.041781 0.022046 -1.895 0.05892 .
# female_d1 0.444902 0.157574 2.823 0.00503 **
# race_child22 -0.094540 0.050158 -1.885 0.06031 .
# race_child23 -0.058228 0.064830 -0.898 0.36974
# race_child24 0.011614 0.097611 0.119 0.90536
# race_child25 -0.034111 0.047204 -0.723 0.47041
# gestage_wks_deliv_d -0.008956 0.010061 -0.890 0.37399
# age_mom_enroll_d -0.005117 0.003181 -1.609 0.10864
# bmi_mom_prepreg_d -0.002403 0.002909 -0.826 0.40930
# coll_grad1 -0.017781 0.036552 -0.486 0.62695
# nullip1 0.006164 0.030703 0.201 0.84101
# gt70k1 -0.018432 0.032247 -0.572 0.56798
# smk_preg21 0.018538 0.036246 0.511 0.60937
# smk_preg22 -0.066931 0.048176 -1.389 0.16565
# Bcell_GS_cb -3.093082 1.200621 -2.576 0.01041 *
# CD4T_GS_cb -2.771575 1.306603 -2.121 0.03463 *
# CD8T_GS_cb -3.221819 1.193333 -2.700 0.00729 **
# Gran_GS_cb -2.840599 1.231364 -2.307 0.02167 *
# Mono_GS_cb -2.636581 1.240351 -2.126 0.03426 *
# NK_GS_cb -3.649269 1.419091 -2.572 0.01055 *
# nRBC_GS_cb -2.764678 1.135999 -2.434 0.01546 *
# Mn_log2:female_d1 -0.112145 0.038817 -2.889 0.00411 **
summary(lm(cg26462130 ~ Mn_log2*female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal))
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) 1.950696 3.354156 0.582 0.5612
# Mn_log2 0.052536 0.052936 0.992 0.3217
# female_d1 -1.190458 0.378370 -3.146 0.0018 **
# race_child22 0.185743 0.120441 1.542 0.1240
# race_child23 0.062434 0.155672 0.401 0.6886
# race_child24 -0.115980 0.234385 -0.495 0.6210
# race_child25 0.081058 0.113346 0.715 0.4750
# gestage_wks_deliv_d -0.054356 0.024158 -2.250 0.0251 *
# age_mom_enroll_d -0.006812 0.007639 -0.892 0.3732
# bmi_mom_prepreg_d 0.005692 0.006984 0.815 0.4157
# coll_grad1 0.055021 0.087769 0.627 0.5312
# nullip1 -0.024841 0.073724 -0.337 0.7364
# gt70k1 -0.046059 0.077432 -0.595 0.5524
# smk_preg21 -0.047188 0.087034 -0.542 0.5881
# smk_preg22 0.109746 0.115680 0.949 0.3434
# Bcell_GS_cb 1.376018 2.882948 0.477 0.6335
# CD4T_GS_cb 6.959568 3.137434 2.218 0.0272 *
# CD8T_GS_cb 0.561962 2.865449 0.196 0.8446
# Gran_GS_cb 6.342588 2.956769 2.145 0.0327 *
# Mono_GS_cb 6.481299 2.978349 2.176 0.0302 *
# NK_GS_cb 2.620977 3.407542 0.769 0.4423
# nRBC_GS_cb 5.384812 2.727778 1.974 0.0492 *
# Mn_log2:female_d1 0.300272 0.093208 3.222 0.0014 **
summary(lm(cg08904630 ~ Mn_log2*female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal))
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) -9.533019 1.796146 -5.307 2.02e-07 ***
# Mn_log2 -0.001419 0.028347 -0.050 0.960
# female_d1 -0.811811 0.202617 -4.007 7.58e-05 ***
# race_child22 0.021232 0.064496 0.329 0.742
# race_child23 -0.038259 0.083362 -0.459 0.647
# race_child24 -0.024295 0.125513 -0.194 0.847
# race_child25 -0.039943 0.060697 -0.658 0.511
# gestage_wks_deliv_d 0.008160 0.012936 0.631 0.529
# age_mom_enroll_d -0.001925 0.004091 -0.470 0.638
# bmi_mom_prepreg_d 0.003719 0.003740 0.994 0.321
# coll_grad1 0.068310 0.047000 1.453 0.147
# nullip1 -0.026822 0.039479 -0.679 0.497
# gt70k1 -0.045652 0.041465 -1.101 0.272
# smk_preg21 0.060623 0.046607 1.301 0.194
# smk_preg22 -0.020541 0.061946 -0.332 0.740
# Bcell_GS_cb 14.101623 1.543815 9.134 < 2e-16 ***
# CD4T_GS_cb 14.075148 1.680092 8.378 1.46e-15 ***
# CD8T_GS_cb 13.890022 1.534444 9.052 < 2e-16 ***
# Gran_GS_cb 13.842205 1.583345 8.742 < 2e-16 ***
# Mono_GS_cb 12.897747 1.594901 8.087 1.11e-14 ***
# NK_GS_cb 14.121618 1.824734 7.739 1.17e-13 ***
# nRBC_GS_cb 9.798080 1.460721 6.708 8.33e-11 ***
# Mn_log2:female_d1 0.201613 0.049913 4.039 6.64e-05 ***
summary(lm(cg22799518 ~ Mn_log2*female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal))
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) -0.708199 4.082573 -0.173 0.86239
# Mn_log2 -0.090490 0.064432 -1.404 0.16111
# female_d1 -2.261018 0.460540 -4.909 1.42e-06 ***
# race_child22 -0.064450 0.146597 -0.440 0.66048
# race_child23 -0.102794 0.189479 -0.543 0.58782
# race_child24 -0.552967 0.285286 -1.938 0.05342 .
# race_child25 -0.226607 0.137962 -1.643 0.10141
# gestage_wks_deliv_d -0.002956 0.029404 -0.101 0.91999
# age_mom_enroll_d -0.001402 0.009298 -0.151 0.88020
# bmi_mom_prepreg_d 0.002804 0.008501 0.330 0.74174
# coll_grad1 -0.082518 0.106829 -0.772 0.44040
# nullip1 0.113216 0.089735 1.262 0.20794
# gt70k1 0.075307 0.094248 0.799 0.42484
# smk_preg21 0.118880 0.105935 1.122 0.26257
# smk_preg22 -0.289512 0.140802 -2.056 0.04053 *
# Bcell_GS_cb 9.501616 3.509034 2.708 0.00712 **
# CD4T_GS_cb 6.973902 3.818786 1.826 0.06870 .
# CD8T_GS_cb 9.197588 3.487734 2.637 0.00875 **
# Gran_GS_cb 7.078108 3.598886 1.967 0.05003 .
# Mono_GS_cb 4.063570 3.625152 1.121 0.26311
# NK_GS_cb 7.530022 4.147552 1.816 0.07033 .
# nRBC_GS_cb 6.507717 3.320165 1.960 0.05081 .
# Mn_log2:female_d1 0.562089 0.113450 4.955 1.15e-06 ***
summary(lm(cg01744822 ~ Mn_log2*female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal))
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) -6.622745 1.919126 -3.451 0.000630 ***
# Mn_log2 -0.040108 0.030288 -1.324 0.186331
# female_d1 0.855571 0.216489 3.952 9.44e-05 ***
# race_child22 0.159105 0.068912 2.309 0.021556 *
# race_child23 0.120227 0.089070 1.350 0.177982
# race_child24 -0.074516 0.134106 -0.556 0.578817
# race_child25 -0.016529 0.064853 -0.255 0.798973
# gestage_wks_deliv_d -0.004849 0.013822 -0.351 0.725971
# age_mom_enroll_d 0.001354 0.004371 0.310 0.756994
# bmi_mom_prepreg_d -0.003337 0.003996 -0.835 0.404322
# coll_grad1 -0.060793 0.050218 -1.211 0.226906
# nullip1 -0.018412 0.042182 -0.436 0.662756
# gt70k1 0.023417 0.044304 0.529 0.597460
# smk_preg21 -0.003833 0.049798 -0.077 0.938688
# smk_preg22 -0.079608 0.066188 -1.203 0.229914
# Bcell_GS_cb 0.245758 1.649518 0.149 0.881652
# CD4T_GS_cb 2.229988 1.795126 1.242 0.215007
# CD8T_GS_cb 2.709826 1.639506 1.653 0.099294 .
# Gran_GS_cb 2.368893 1.691756 1.400 0.162354
# Mono_GS_cb 4.173759 1.704103 2.449 0.014823 *
# NK_GS_cb 2.302494 1.949672 1.181 0.238447
# nRBC_GS_cb 1.964726 1.560736 1.259 0.208955
# Mn_log2:female_d1 -0.180845 0.053330 -3.391 0.000779 ***
summary(lm(cg15712310 ~ Mn_log2*female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal))
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) -1.074e+01 1.592e+00 -6.743 6.74e-11 ***
# Mn_log2 -3.012e-02 2.513e-02 -1.199 0.231532
# female_d1 8.028e-01 1.796e-01 4.469 1.07e-05 ***
# race_child22 1.150e-01 5.718e-02 2.010 0.045173 *
# race_child23 5.358e-02 7.391e-02 0.725 0.468978
# race_child24 -1.244e-01 1.113e-01 -1.118 0.264452
# race_child25 -3.747e-02 5.381e-02 -0.696 0.486745
# gestage_wks_deliv_d 4.583e-02 1.147e-02 3.996 7.92e-05 ***
# age_mom_enroll_d -7.518e-04 3.627e-03 -0.207 0.835900
# bmi_mom_prepreg_d -4.946e-03 3.316e-03 -1.491 0.136765
# coll_grad1 -2.884e-02 4.167e-02 -0.692 0.489332
# nullip1 -5.193e-02 3.500e-02 -1.484 0.138843
# gt70k1 -2.305e-02 3.676e-02 -0.627 0.531152
# smk_preg21 -3.881e-02 4.132e-02 -0.939 0.348225
# smk_preg22 -6.084e-03 5.492e-02 -0.111 0.911858
# Bcell_GS_cb 4.796e+00 1.369e+00 3.504 0.000520 ***
# CD4T_GS_cb 7.066e+00 1.490e+00 4.744 3.10e-06 ***
# CD8T_GS_cb 6.006e+00 1.360e+00 4.415 1.36e-05 ***
# Gran_GS_cb 7.190e+00 1.404e+00 5.122 5.10e-07 ***
# Mono_GS_cb 7.275e+00 1.414e+00 5.145 4.54e-07 ***
# NK_GS_cb 6.728e+00 1.618e+00 4.159 4.07e-05 ***
# nRBC_GS_cb 6.262e+00 1.295e+00 4.835 2.02e-06 ***
# Mn_log2:female_d1 -1.571e-01 4.425e-02 -3.551 0.000438 ***
summary(lm(cg03763518 ~ Mn_log2*female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal))
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) -5.556886 3.530716 -1.574 0.11645
# Mn_log2 -0.282677 0.055723 -5.073 6.48e-07 ***
# female_d1 -1.050888 0.398287 -2.639 0.00871 **
# race_child22 0.004720 0.126781 0.037 0.97032
# race_child23 -0.130568 0.163866 -0.797 0.42613
# race_child24 -0.325536 0.246723 -1.319 0.18791
# race_child25 -0.017700 0.119313 -0.148 0.88215
# gestage_wks_deliv_d 0.047989 0.025429 1.887 0.05999 .
# age_mom_enroll_d -0.005685 0.008041 -0.707 0.48005
# bmi_mom_prepreg_d 0.005167 0.007352 0.703 0.48267
# coll_grad1 -0.048079 0.092389 -0.520 0.60313
# nullip1 -0.023860 0.077605 -0.307 0.75869
# gt70k1 0.062339 0.081508 0.765 0.44491
# smk_preg21 -0.077923 0.091615 -0.851 0.39563
# smk_preg22 0.172928 0.121769 1.420 0.15649
# Bcell_GS_cb 0.341955 3.034705 0.113 0.91035
# CD4T_GS_cb 4.776430 3.302587 1.446 0.14903
# CD8T_GS_cb 4.607262 3.016284 1.527 0.12758
# Gran_GS_cb 0.424865 3.112411 0.137 0.89150
# Mono_GS_cb -0.098276 3.135127 -0.031 0.97501
# NK_GS_cb 1.852012 3.586912 0.516 0.60597
# nRBC_GS_cb 0.913396 2.871366 0.318 0.75060
# Mn_log2:female_d1 0.278244 0.098114 2.836 0.00484 **
FDR-significant DMPs
|
|
cpg
|
logFC_CI
|
AveExpr
|
P.Value
|
adj.P.Val
|
adj.P.Val.bonf
|
chr
|
pos
|
gene
|
|
34177
|
cg02042823
|
0.43 (0.31 ,0.55)
|
5.75
|
0
|
9.7e-06
|
0
|
chr16
|
6714429
|
A2BP1;A2BP1
|
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
6
|
32063725
|
32064161
|
0.0000000
|
436
|
0.0000000
|
0.0000020
|
13
|
|
7
|
1250125
|
1250182
|
0.0016611
|
57
|
0.0016611
|
0.9999899
|
2
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_smk/Mn_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_smk/Mn_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_smk/Mn_log2_manhattan_DMP_adj.png")
Mn, female
DMP_Mn_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Mn_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_F_smk')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 26444
# Unadjusted, FDR<0.05: 3
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 169
# Adjusted, p<0.05: 13124
# Adjusted, FDR<0.05: 9
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.8902733
# Number of DMRs identified: 7
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_F)
y = pDatcordMetal_F$Mn_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_F)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.352921
TestCDFs2(Z = Z, y = y, X = X)
# 0.7004179
DMP_Mn_F_cord[[3]] = NULL
# limma on Beta-values
DMP_Mn_F_cord_beta = run_EWAS(DNAm = ComBat.Betas.Metals, pheno = pDatcordMetal_F, var = 'Mn_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_F_smk_beta')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 23593
# Unadjusted, FDR<0.05: 94
# Unadjusted, pBonf<0.05: 34
# Adjusted, N = 169
# Adjusted, p<0.05: 14214
# Adjusted, FDR<0.05: 92
# Adjusted, pBonf<0.05: 33
# Adjusted, lambda: 0.8252193
# Number of DMRs identified: 17
DMP_Mn_F_cord_beta[[3]][DMP_Mn_F_cord_beta[[3]]$cpg == 'cg00954161',c(2:4)]*100
# logFC CI.L CI.R
# cg00954161 1.542443 1.07827 2.006615
DMP_Mn_F_cord_beta[[3]][DMP_Mn_F_cord_beta[[3]]$cpg == 'cg11161853',c(2:4)]*100
# logFC CI.L CI.R
# cg11161853 -0.3248247 -0.4268515 -0.2227979
DMP_Mn_F_cord_beta[[3]][DMP_Mn_F_cord_beta[[3]]$cpg == 'cg23903787',c(2:4)]*100
# logFC CI.L CI.R
# cg23903787 4.600704 3.322436 5.878972
DMP_Mn_F_cord_beta[[3]][DMP_Mn_F_cord_beta[[3]]$cpg == 'cg19908812',c(2:4)]*100
# logFC CI.L CI.R
# cg19908812 -0.2957255 -0.3764997 -0.2149513
DMP_Mn_F_cord_beta[[3]][DMP_Mn_F_cord_beta[[3]]$cpg == 'cg26462130',c(2:4)]*100
# logFC CI.L CI.R
# cg26462130 2.04333 1.674487 2.412172
DMP_Mn_F_cord_beta[[3]][DMP_Mn_F_cord_beta[[3]]$cpg == 'cg08904630',c(2:4)]*100
# logFC CI.L CI.R
# cg08904630 0.8392856 0.6361831 1.042388
DMP_Mn_F_cord_beta[[3]][DMP_Mn_F_cord_beta[[3]]$cpg == 'cg22799518',c(2:4)]*100
# logFC CI.L CI.R
# cg22799518 2.0281 1.620137 2.436062
DMP_Mn_F_cord_beta[[3]][DMP_Mn_F_cord_beta[[3]]$cpg == 'cg01744822',c(2:4)]*100
# logFC CI.L CI.R
# cg01744822 -1.156249 -1.454187 -0.8583115
DMP_Mn_F_cord_beta[[3]][DMP_Mn_F_cord_beta[[3]]$cpg == 'cg15712310',c(2:4)]*100
# logFC CI.L CI.R
# cg15712310 -2.685899 -3.558376 -1.813422
rm(DMP_Mn_F_cord_beta)
FDR-significant DMPs
|
|
cpg
|
logFC_CI
|
AveExpr
|
P.Value
|
adj.P.Val
|
adj.P.Val.bonf
|
chr
|
pos
|
gene
|
|
16391
|
cg00954161
|
0.42 (0.26 ,0.57)
|
5.99
|
2.0e-07
|
0.0374428
|
0.0881
|
chr1
|
3696925
|
LRRC47
|
|
29171
|
cg01744822
|
-0.22 (-0.31 ,-0.14)
|
-4.36
|
9.0e-07
|
0.0481639
|
0.3625
|
chr16
|
73100510
|
|
|
140511
|
cg08904630
|
0.21 (0.13 ,0.29)
|
5.33
|
9.0e-07
|
0.0481639
|
0.3714
|
chr10
|
71490427
|
|
|
172088
|
cg11161853
|
-0.14 (-0.19 ,-0.08)
|
-5.29
|
1.0e-06
|
0.0481639
|
0.4082
|
chr3
|
67705044
|
SUCLG2
|
|
237397
|
cg15712310
|
-0.19 (-0.26 ,-0.12)
|
-1.62
|
2.0e-07
|
0.0374428
|
0.0763
|
chr16
|
73100790
|
|
|
293403
|
cg19908812
|
-0.17 (-0.24 ,-0.1)
|
-6.02
|
9.0e-07
|
0.0481639
|
0.3693
|
chr4
|
164253006
|
NPY1R
|
|
328975
|
cg22799518
|
0.52 (0.33 ,0.71)
|
6.34
|
4.0e-07
|
0.0374428
|
0.1498
|
chr12
|
56988862
|
RBMS2
|
|
343691
|
cg23903787
|
0.34 (0.21 ,0.47)
|
3.02
|
3.0e-07
|
0.0374428
|
0.1233
|
chr4
|
3527371
|
LRPAP1
|
|
377542
|
cg26462130
|
0.38 (0.24 ,0.53)
|
6.11
|
1.1e-06
|
0.0481639
|
0.4335
|
chr7
|
2052961
|
MAD1L1;MAD1L1;MAD1L1
|
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
16
|
73100425
|
73100790
|
0e+00
|
365
|
0e+00
|
0.0000000
|
3
|
|
3
|
148804271
|
148804556
|
0e+00
|
285
|
0e+00
|
0.0000004
|
8
|
|
3
|
67704889
|
67705285
|
0e+00
|
396
|
0e+00
|
0.0000005
|
6
|
|
6
|
161561030
|
161561121
|
0e+00
|
91
|
0e+00
|
0.0000076
|
3
|
|
7
|
3019158
|
3019382
|
0e+00
|
224
|
0e+00
|
0.0000051
|
4
|
|
7
|
27170716
|
27171051
|
0e+00
|
335
|
0e+00
|
0.0000040
|
9
|
|
13
|
97646638
|
97646765
|
6e-07
|
127
|
6e-07
|
0.0017938
|
4
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_F_smk/Mn_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_F_smk/Mn_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_F_smk/Mn_log2_manhattan_DMP_adj.png")
Mn, male
DMP_Mn_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Mn_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_M_smk')
# # Unadjusted, N = 192
# Unadjusted, p<0.05: 9543
# Unadjusted, FDR<0.05: 2
# Unadjusted, pBonf<0.05: 2
# Adjusted, N = 192
# Adjusted, p<0.05: 12768
# Adjusted, FDR<0.05: 2
# Adjusted, pBonf<0.05: 2
# Adjusted, lambda: 0.8373675
# Number of DMRs identified: 4
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_M)
y = pDatcordMetal_M$Mn_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_M)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.375884
TestCDFs2(Z = Z, y = y, X = X)
# 0.5432648
DMP_Mn_M_cord[[3]] = NULL
# limma on Beta-values
DMP_Mn_M_cord_beta = run_EWAS(DNAm = ComBat.Betas.Metals, pheno = pDatcordMetal_M, var = 'Mn_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_M_smk_beta')
# Unadjusted, N = 192
# Unadjusted, p<0.05: 9426
# Unadjusted, FDR<0.05: 88
# Unadjusted, pBonf<0.05: 22
# Adjusted, N = 192
# Adjusted, p<0.05: 13470
# Adjusted, FDR<0.05: 106
# Adjusted, pBonf<0.05: 27
# Adjusted, lambda: 0.8445073
# Number of DMRs identified: 16
DMP_Mn_M_cord_beta[[3]][DMP_Mn_M_cord_beta[[3]]$cpg == 'cg03763518',c(2:4)]*100
# logFC CI.L CI.R
# cg03763518 -3.008463 -3.718318 -2.298607
DMP_Mn_M_cord_beta[[3]][DMP_Mn_M_cord_beta[[3]]$cpg == 'cg02042823',c(2:4)]*100
# logFC CI.L CI.R
# cg02042823 3.396064 2.726415 4.065714
rm(DMP_Mn_M_cord_beta)
FDR-significant DMPs
|
|
cpg
|
logFC_CI
|
AveExpr
|
P.Value
|
adj.P.Val
|
adj.P.Val.bonf
|
chr
|
pos
|
gene
|
|
34177
|
cg02042823
|
0.51 (0.36 ,0.66)
|
5.71
|
0
|
0.0001100
|
0.0001
|
chr16
|
6714429
|
A2BP1;A2BP1
|
|
62243
|
cg03763518
|
-0.29 (-0.39 ,-0.19)
|
-3.51
|
0
|
0.0093594
|
0.0187
|
chr1
|
150245044
|
C1orf54
|
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
20
|
36148603
|
36149271
|
0.0000000
|
668
|
0.0000000
|
0.0e+00
|
31
|
|
7
|
1250087
|
1250273
|
0.0000000
|
186
|
0.0000000
|
0.0e+00
|
7
|
|
15
|
99789621
|
99789855
|
0.0000000
|
234
|
0.0000000
|
5.2e-06
|
5
|
|
1
|
75198817
|
75198841
|
0.0012361
|
24
|
0.0012361
|
1.0e+00
|
2
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_M_smk/Mn_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_M_smk/Mn_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Mn_M_smk/Mn_log2_manhattan_DMP_adj.png")
Pb
DMP_Pb_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Pb_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_smk')
Unadjusted, N = 361
Unadjusted, p<0.05: 25856
Unadjusted, FDR<0.05: 0
Unadjusted, pBonf<0.05: 0
Adjusted, N = 361
Adjusted, p<0.05: 15400
Adjusted, FDR<0.05: 1
Adjusted, pBonf<0.05: 1
Adjusted, lambda: 0.9055461
Number of identified DMR: 0
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals)
y = pDatcordMetal$Pb_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.1927262
TestCDFs2(Z = Z, y = y, X = X)
# 0.5246463
DMP_Pb_cord[[3]] = NULL
# limma using Beta-values
DMP_Pb_cord_beta = run_EWAS(DNAm = ComBat.Betas.Metals, pheno = pDatcordMetal, var = 'Pb_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_smk_beta')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 28387
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 361
# Adjusted, p<0.05: 15426
# Adjusted, FDR<0.05: 1
# Adjusted, pBonf<0.05: 1
# Adjusted, lambda: 0.9230217
# Number of DMRs identified: 1
DMP_Pb_cord_beta[[3]][DMP_Pb_cord_beta[[3]]$cpg == 'cg20608990',c(2:4)]*100
# logFC CI.L CI.R
# cg20608990 -3.096945 -4.218935 -1.974954
FDR-significant DMPs
|
|
cpg
|
logFC_CI
|
AveExpr
|
P.Value
|
adj.P.Val
|
adj.P.Val.bonf
|
chr
|
pos
|
gene
|
|
302067
|
cg20608990
|
-0.2 (-0.28 ,-0.13)
|
0.9
|
1e-07
|
0.0403092
|
0.0403
|
chr2
|
202097607
|
CASP8;CASP8;CASP8;CASP8
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_smk/Pb_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_smk/Pb_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_smk/Pb_log2_manhattan_DMP_adj.png")
Pb, female
DMP_Pb_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Pb_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_F_smk')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 16597
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 169
# Adjusted, p<0.05: 20040
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.107063
# Number of identified DMR: 0
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_F)
y = pDatcordMetal_F$Pb_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_F)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.0685342
TestCDFs2(Z = Z, y = y, X = X)
# 0.2663275
DMP_Pb_F_cord[[3]] = NULL
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_F_smk/Pb_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_F_smk/Pb_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_F_smk/Pb_log2_manhattan_DMP_adj.png")
Pb, male
DMP_Pb_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Pb_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_M_smk')
# # Unadjusted, N = 192
# Unadjusted, p<0.05: 19998
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 192
# Adjusted, p<0.05: 13991
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.8777486
# Number of DMRs identified: 2
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_M)
y = pDatcordMetal_M$Pb_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_M)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.9185112
TestCDFs2(Z = Z, y = y, X = X)
# 0.875775
DMP_Pb_M_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
14
|
100203941
|
100204258
|
0
|
317
|
0
|
5.00e-07
|
6
|
|
3
|
122640777
|
122641144
|
0
|
367
|
0
|
1.36e-05
|
4
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_M_smk/Pb_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_M_smk/Pb_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Pb_M_smk/Pb_log2_manhattan_DMP_adj.png")
Se
DMP_Se_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Se_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_smk')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 23447
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 361
# Adjusted, p<0.05: 15944
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.8650339
# Number of DMRs identified: 2
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals)
y = pDatcordMetal$Se_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.1199839
TestCDFs2(Z = Z, y = y, X = X)
# 0.2784228
DMP_Se_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
8
|
144635259
|
144635610
|
0
|
351
|
0
|
8.70e-06
|
9
|
|
4
|
74847645
|
74847829
|
0
|
184
|
0
|
4.24e-05
|
7
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_smk/Se_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_smk/Se_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_smk/Se_log2_manhattan_DMP_adj.png")
Se, female
DMP_Se_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Se_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_F_smk')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 11702
# Unadjusted, FDR<0.05: 1
# Unadjusted, pBonf<0.05: 1
# Adjusted, N = 169
# Adjusted, p<0.05: 10681
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 0.7154979
# Number of DMRs identified: 4
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_F)
y = pDatcordMetal_F$Se_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_F)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.6477685
TestCDFs2(Z = Z, y = y, X = X)
# 0.8642817
DMP_Se_F_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
8
|
144635259
|
144636113
|
0.0000000
|
854
|
0.0000000
|
0.0000000
|
12
|
|
15
|
75019086
|
75019376
|
0.0000000
|
290
|
0.0000000
|
0.0000143
|
9
|
|
19
|
1510493
|
1510692
|
0.0000001
|
199
|
0.0000001
|
0.0001064
|
4
|
|
18
|
23713837
|
23714009
|
0.0002357
|
172
|
0.0002357
|
0.4176575
|
3
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_F_smk/Se_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_F_smk/Se_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_F_smk/Se_log2_manhattan_DMP_adj.png")
Se, male
DMP_Se_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Se_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_M_smk')
# Unadjusted, N = 192
# Unadjusted, p<0.05: 28127
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 192
# Adjusted, p<0.05: 21716
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.00727
# Number of DMRs identified: 1
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_M)
y = pDatcordMetal_M$Se_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_M)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.06037239
TestCDFs2(Z = Z, y = y, X = X)
# 0.1802247
DMP_Se_M_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
19
|
57742254
|
57742423
|
0
|
169
|
0
|
1.63e-05
|
6
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_M_smk/Se_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_M_smk/Se_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Se_M_smk/Se_log2_manhattan_DMP_adj.png")
Zn
DMP_Zn_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal, var = 'Zn_log2', covar = c('female_d', 'race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_smk')
# Unadjusted, N = 361
# Unadjusted, p<0.05: 25089
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 361
# Adjusted, p<0.05: 37298
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.482864
# Number of DMRs identified: 6
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals)
y = pDatcordMetal$Zn_log2
X = model.matrix(~ female_d + race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.6866896
TestCDFs2(Z = Z, y = y, X = X)
# 0.227695
DMP_Zn_cord[[3]] = NULL
DMRs
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
3
|
48632483
|
48632783
|
0.00e+00
|
300
|
0.00e+00
|
0.0000006
|
8
|
|
17
|
79503641
|
79503877
|
0.00e+00
|
236
|
0.00e+00
|
0.0000011
|
4
|
|
12
|
1973871
|
1974168
|
0.00e+00
|
297
|
0.00e+00
|
0.0000068
|
3
|
|
11
|
92702372
|
92702912
|
0.00e+00
|
540
|
0.00e+00
|
0.0000069
|
8
|
|
20
|
25129506
|
25129562
|
4.70e-06
|
56
|
5.70e-06
|
0.0326938
|
5
|
|
6
|
32165175
|
32165200
|
5.34e-05
|
25
|
5.34e-05
|
0.5696028
|
3
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_smk/Zn_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_smk/Zn_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_smk/Zn_log2_manhattan_DMP_adj.png")
Zn, female
DMP_Zn_F_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_F, var = 'Zn_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_F_smk')
# Unadjusted, N = 169
# Unadjusted, p<0.05: 35062
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 169
# Adjusted, p<0.05: 16490
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.041223
# Number of identified DMR: 0
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_F)
y = pDatcordMetal_F$Zn_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_F)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.5957239
TestCDFs2(Z = Z, y = y, X = X)
# 0.2421123
DMP_Zn_F_cord[[3]] = NULL
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_F_smk/Zn_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_F_smk/Zn_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_F_smk/Zn_log2_manhattan_DMP_adj.png")
Zn, male
DMP_Zn_M_cord = run_EWAS(DNAm = ComBat.Mvalues.Metals, pheno = pDatcordMetal_M, var = 'Zn_log2', covar = c('race_child2', 'gestage_wks_deliv_d', 'age_mom_enroll_d', 'bmi_mom_prepreg_d', 'coll_grad', 'nullip', 'gt70k', 'smk_preg2', 'Bcell_GS_cb', 'CD4T_GS_cb', 'CD8T_GS_cb', 'Gran_GS_cb', 'Mono_GS_cb', 'NK_GS_cb', 'nRBC_GS_cb'), anno = anno, path = '/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_M_smk')
# Unadjusted, N = 192
# Unadjusted, p<0.05: 10405
# Unadjusted, FDR<0.05: 0
# Unadjusted, pBonf<0.05: 0
# Adjusted, N = 192
# Adjusted, p<0.05: 21836
# Adjusted, FDR<0.05: 0
# Adjusted, pBonf<0.05: 0
# Adjusted, lambda: 1.096011
# Number of DMRs identified: 4
# Global DNAm
Z = as.matrix(ComBat.Betas.Metals_M)
y = pDatcordMetal_M$Zn_log2
X = model.matrix(~ race_child2 + gestage_wks_deliv_d + age_mom_enroll_d + bmi_mom_prepreg_d + coll_grad + nullip + gt70k + smk_preg2 + Bcell_GS_cb + CD4T_GS_cb + CD8T_GS_cb + Gran_GS_cb + Mono_GS_cb + NK_GS_cb + nRBC_GS_cb, data = pDatcordMetal_M)[,-1]
TestDensities2(Z = Z, y = y, X = X)
# 0.8743051
TestCDFs2(Z = Z, y = y, X = X)
# 0.7396624
DMP_Zn_M_cord[[3]] = NULL
|
chr
|
start
|
end
|
p
|
length
|
fdr
|
sidak
|
nprobe
|
|
13
|
110319561
|
110319607
|
0.0000000
|
46
|
0.0000000
|
1.70e-05
|
3
|
|
5
|
112824496
|
112824765
|
0.0000000
|
269
|
0.0000000
|
1.30e-05
|
6
|
|
1
|
1361654
|
1361729
|
0.0000000
|
75
|
0.0000000
|
6.26e-05
|
3
|
|
6
|
31651019
|
31651029
|
0.0083115
|
10
|
0.0083115
|
1.00e+00
|
2
|
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_M_smk/Zn_log2_QQ_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_M_smk/Zn_log2_volcano_DMP_adj.png")
knitr::include_graphics("/Users/annebozack/Documents/Cardenas/viva_DNAm_metals_local/CordBlood/Zn_M_smk/Zn_log2_manhattan_DMP_adj.png")
GO regional analysis
Combining all regions across metals before running goRegion
# DMRs = rbind(DMP_As_cord[[2]], DMP_As_F_cord[[2]], DMP_As_M_cord[[2]], DMP_Ba_F_cord[[2]], DMP_Ba_M_cord[[2]], DMP_Cd_cord[[2]], DMP_Cd_F_cord[[2]], DMP_Cd_M_cord[[2]], DMP_Cr_cord[[2]], DMP_Cr_F_cord[[2]], DMP_Cs_cord[[2]], DMP_Cs_F_cord[[2]], DMP_Cs_M_cord[[2]], DMP_Cu_cord[[2]], DMP_Cu_F_cord[[2]], DMP_Cu_M_cord[[2]], DMP_Hg_cord[[2]], DMP_Hg_M_cord[[2]], DMP_Mg_cord[[2]], DMP_Mg_F_cord[[2]], DMP_Mg_M_cord[[2]], DMP_Mn_cord[[2]], DMP_Mn_F_cord[[2]], DMP_Mn_M_cord[[2]], DMP_Pb_M_cord[[2]], DMP_Se_cord[[2]], DMP_Se_F_cord[[2]], DMP_Se_M_cord[[2]], DMP_Zn_cord[[2]], DMP_Zn_M_cord[[2]])
DMRs = rbind(DMP_As_cord[[2]], DMP_Cd_cord[[2]], DMP_Cr_cord[[2]], DMP_Cs_cord[[2]], DMP_Cu_cord[[2]], DMP_Hg_cord[[2]], DMP_Mg_cord[[2]], DMP_Mn_cord[[2]], DMP_Se_cord[[2]], DMP_Zn_cord[[2]])
DMRs$chr = paste0('chr', DMRs$chr)
dim(DMRs)
# 50 8
DMRs = DMRs[!duplicated(DMRs[,c(1:3)]),]
dim(DMRs)
# 50 8
DMRs = makeGRangesFromDataFrame(DMRs, keep.extra.columns = T, start.field = 'start', end.field = 'end')
go_region_metals <- goregion(DMRs, all.cpg=rownames(ComBat.Mvalues.Metals), collection="GO", array.type="450K", plot.bias=TRUE)
table(go_region_metals$P.DE < 0.05 & go_region_metals$DE > 1)
FALSE TRUE
22559 51
|
|
ONTOLOGY
|
TERM
|
N
|
DE
|
P.DE
|
FDR
|
|
GO:0000139
|
CC
|
Golgi membrane
|
711
|
5
|
0.0328031
|
1
|
|
GO:0001501
|
BP
|
skeletal system development
|
499
|
5
|
0.0287860
|
1
|
|
GO:0002376
|
BP
|
immune system process
|
2809
|
12
|
0.0159911
|
1
|
|
GO:0002520
|
BP
|
immune system development
|
976
|
6
|
0.0437519
|
1
|
|
GO:0002761
|
BP
|
regulation of myeloid leukocyte differentiation
|
120
|
2
|
0.0415919
|
1
|
|
GO:0002763
|
BP
|
positive regulation of myeloid leukocyte differentiation
|
57
|
2
|
0.0083892
|
1
|
|
GO:0003697
|
MF
|
single-stranded DNA binding
|
110
|
2
|
0.0195434
|
1
|
|
GO:0005102
|
MF
|
signaling receptor binding
|
1474
|
8
|
0.0289993
|
1
|
|
GO:0005654
|
CC
|
nucleoplasm
|
3748
|
15
|
0.0299610
|
1
|
|
GO:0005793
|
CC
|
endoplasmic reticulum-Golgi intermediate compartment
|
123
|
2
|
0.0391497
|
1
|
|
GO:0006112
|
BP
|
energy reserve metabolic process
|
81
|
2
|
0.0222137
|
1
|
|
GO:0006259
|
BP
|
DNA metabolic process
|
890
|
7
|
0.0022239
|
1
|
|
GO:0006281
|
BP
|
DNA repair
|
531
|
4
|
0.0234289
|
1
|
|
GO:0006289
|
BP
|
nucleotide-excision repair
|
106
|
2
|
0.0171749
|
1
|
|
GO:0006304
|
BP
|
DNA modification
|
116
|
2
|
0.0255831
|
1
|
|
GO:0006950
|
BP
|
response to stress
|
3816
|
15
|
0.0151450
|
1
|
|
GO:0006974
|
BP
|
cellular response to DNA damage stimulus
|
820
|
7
|
0.0023348
|
1
|
|
GO:0007187
|
BP
|
G protein-coupled receptor signaling pathway, coupled to cyclic nucleotide second messenger
|
251
|
3
|
0.0225996
|
1
|
|
GO:0007189
|
BP
|
adenylate cyclase-activating G protein-coupled receptor signaling pathway
|
142
|
2
|
0.0440550
|
1
|
|
GO:0007599
|
BP
|
hemostasis
|
323
|
4
|
0.0129205
|
1
|
|
GO:0008194
|
MF
|
UDP-glycosyltransferase activity
|
134
|
2
|
0.0407303
|
1
|
|
GO:0008376
|
MF
|
acetylgalactosaminyltransferase activity
|
46
|
2
|
0.0087394
|
1
|
|
GO:0010467
|
BP
|
gene expression
|
6132
|
19
|
0.0314445
|
1
|
|
GO:0016050
|
BP
|
vesicle organization
|
326
|
3
|
0.0429370
|
1
|
|
GO:0016605
|
CC
|
PML body
|
98
|
2
|
0.0337088
|
1
|
|
GO:0019935
|
BP
|
cyclic-nucleotide-mediated signaling
|
217
|
3
|
0.0188825
|
1
|
|
GO:0030097
|
BP
|
hemopoiesis
|
881
|
6
|
0.0276998
|
1
|
|
GO:0030099
|
BP
|
myeloid cell differentiation
|
410
|
4
|
0.0260155
|
1
|
|
GO:0030219
|
BP
|
megakaryocyte differentiation
|
92
|
2
|
0.0248782
|
1
|
|
GO:0032940
|
BP
|
secretion by cell
|
1359
|
7
|
0.0492601
|
1
|
|
GO:0032993
|
CC
|
protein-DNA complex
|
182
|
2
|
0.0420900
|
1
|
|
GO:0033116
|
CC
|
endoplasmic reticulum-Golgi intermediate compartment membrane
|
71
|
2
|
0.0142894
|
1
|
|
GO:0033554
|
BP
|
cellular response to stress
|
1994
|
10
|
0.0180330
|
1
|
|
GO:0034641
|
BP
|
cellular nitrogen compound metabolic process
|
6355
|
20
|
0.0308302
|
1
|
|
GO:0042169
|
MF
|
SH2 domain binding
|
40
|
2
|
0.0078222
|
1
|
|
GO:0042581
|
CC
|
specific granule
|
151
|
2
|
0.0422568
|
1
|
|
GO:0043170
|
BP
|
macromolecule metabolic process
|
9576
|
28
|
0.0159128
|
1
|
|
GO:0045639
|
BP
|
positive regulation of myeloid cell differentiation
|
96
|
2
|
0.0262081
|
1
|
|
GO:0045944
|
BP
|
positive regulation of transcription by RNA polymerase II
|
1143
|
8
|
0.0240330
|
1
|
|
GO:0046883
|
BP
|
regulation of hormone secretion
|
257
|
3
|
0.0434351
|
1
|
|
GO:0048534
|
BP
|
hematopoietic or lymphoid organ development
|
922
|
6
|
0.0364718
|
1
|
|
GO:0048704
|
BP
|
embryonic skeletal system morphogenesis
|
96
|
3
|
0.0095150
|
1
|
|
GO:0048706
|
BP
|
embryonic skeletal system development
|
128
|
3
|
0.0191970
|
1
|
|
GO:0050878
|
BP
|
regulation of body fluid levels
|
482
|
4
|
0.0441046
|
1
|
|
GO:0060255
|
BP
|
regulation of macromolecule metabolic process
|
6359
|
21
|
0.0347611
|
1
|
|
GO:0070491
|
MF
|
repressing transcription factor binding
|
71
|
2
|
0.0212427
|
1
|
|
GO:0090304
|
BP
|
nucleic acid metabolic process
|
5141
|
17
|
0.0397671
|
1
|
|
GO:0097530
|
BP
|
granulocyte migration
|
142
|
2
|
0.0223789
|
1
|
|
GO:1990266
|
BP
|
neutrophil migration
|
115
|
2
|
0.0141909
|
1
|
|
GO:2001234
|
BP
|
negative regulation of apoptotic signaling pathway
|
220
|
3
|
0.0176248
|
1
|
|
GO:2001237
|
BP
|
negative regulation of extrinsic apoptotic signaling pathway
|
101
|
2
|
0.0367395
|
1
|
As
As = DMP_As_cord[[2]]
As$chr = paste0('chr', As$chr)
As = makeGRangesFromDataFrame(As, keep.extra.columns = T, start.field = 'start', end.field = 'end')
go_region_metals_As <- goregion(As, all.cpg=rownames(ComBat.Mvalues.Metals), collection="GO", array.type="450K", plot.bias=TRUE, anno = anno)
# There are no genes annotated to the significant CpGs
Cd
Cd = DMP_Cd_cord[[2]]
Cd$chr = paste0('chr', Cd$chr)
Cd = makeGRangesFromDataFrame(Cd, keep.extra.columns = T, start.field = 'start', end.field = 'end')
go_region_metals_Cd <- goregion(Cd, all.cpg=rownames(ComBat.Mvalues.Metals), collection="GO", array.type="450K", plot.bias=TRUE, anno = anno)
table(go_region_metals_Cd$P.DE < 0.05 & go_region_metals_Cd$DE > 1)
# FALSE TRUE
# 22609 1
|
|
ONTOLOGY
|
TERM
|
N
|
DE
|
P.DE
|
FDR
|
|
GO:0002376
|
BP
|
immune system process
|
2809
|
2
|
0.027361
|
1
|
Cr
go_region_metals_Cr[go_region_metals_Cr$P.DE < 0.05 & go_region_metals_Cr$DE > 1,]Cr = DMP_Cr_cord[[2]]
Cr$chr = paste0('chr', Cr$chr)
Cr = makeGRangesFromDataFrame(Cr, keep.extra.columns = T, start.field = 'start', end.field = 'end')
go_region_metals_Cr <- goregion(Cr, all.cpg=rownames(ComBat.Mvalues.Metals), collection="GO", array.type="450K", plot.bias=TRUE, anno = anno)
table(go_region_metals_Cr$P.DE < 0.05 & go_region_metals_Cr$DE > 1)
# FALSE TRUE
# 22586 24
|
|
ONTOLOGY
|
TERM
|
N
|
DE
|
P.DE
|
FDR
|
|
GO:0000122
|
BP
|
negative regulation of transcription by RNA polymerase II
|
867
|
2
|
0.0434115
|
1
|
|
GO:0000978
|
MF
|
RNA polymerase II cis-regulatory region sequence-specific DNA binding
|
1035
|
2
|
0.0383663
|
1
|
|
GO:0000987
|
MF
|
cis-regulatory region sequence-specific DNA binding
|
1060
|
2
|
0.0419075
|
1
|
|
GO:0001216
|
MF
|
DNA-binding transcription activator activity
|
495
|
2
|
0.0152292
|
1
|
|
GO:0001228
|
MF
|
DNA-binding transcription activator activity, RNA polymerase II-specific
|
492
|
2
|
0.0152289
|
1
|
|
GO:0001568
|
BP
|
blood vessel development
|
748
|
2
|
0.0256703
|
1
|
|
GO:0001944
|
BP
|
vasculature development
|
779
|
2
|
0.0270904
|
1
|
|
GO:0007420
|
BP
|
brain development
|
717
|
2
|
0.0399646
|
1
|
|
GO:0009100
|
BP
|
glycoprotein metabolic process
|
391
|
2
|
0.0039800
|
1
|
|
GO:0009101
|
BP
|
glycoprotein biosynthetic process
|
321
|
2
|
0.0027841
|
1
|
|
GO:0009792
|
BP
|
embryo development ending in birth or egg hatching
|
638
|
2
|
0.0248821
|
1
|
|
GO:0009888
|
BP
|
tissue development
|
2005
|
3
|
0.0191039
|
1
|
|
GO:0019904
|
MF
|
protein domain specific binding
|
670
|
2
|
0.0244037
|
1
|
|
GO:0030902
|
BP
|
hindbrain development
|
148
|
2
|
0.0017297
|
1
|
|
GO:0035239
|
BP
|
tube morphogenesis
|
903
|
2
|
0.0428432
|
1
|
|
GO:0043009
|
BP
|
chordate embryonic development
|
622
|
2
|
0.0239206
|
1
|
|
GO:0048598
|
BP
|
embryonic morphogenesis
|
587
|
2
|
0.0288730
|
1
|
|
GO:0050793
|
BP
|
regulation of developmental process
|
2633
|
3
|
0.0458964
|
1
|
|
GO:0051173
|
BP
|
positive regulation of nitrogen compound metabolic process
|
3009
|
3
|
0.0467637
|
1
|
|
GO:0060322
|
BP
|
head development
|
758
|
2
|
0.0439771
|
1
|
|
GO:0072359
|
BP
|
circulatory system development
|
1133
|
3
|
0.0044613
|
1
|
|
GO:1901135
|
BP
|
carbohydrate derivative metabolic process
|
1061
|
2
|
0.0215445
|
1
|
|
GO:1901137
|
BP
|
carbohydrate derivative biosynthetic process
|
627
|
2
|
0.0091591
|
1
|
|
GO:1901566
|
BP
|
organonitrogen compound biosynthetic process
|
1705
|
2
|
0.0373267
|
1
|
Cs
Cs = DMP_Cs_cord[[2]]
Cs$chr = paste0('chr', Cs$chr)
Cs = makeGRangesFromDataFrame(Cs, keep.extra.columns = T, start.field = 'start', end.field = 'end')
go_region_metals_Cs <- goregion(Cs, all.cpg=rownames(ComBat.Mvalues.Metals), collection="GO", array.type="450K", plot.bias=TRUE, anno = anno)
table(go_region_metals_Cs$P.DE < 0.05 & go_region_metals_Cs$DE > 1)
# FALSE TRUE
# 22590 20
|
|
ONTOLOGY
|
TERM
|
N
|
DE
|
P.DE
|
FDR
|
|
GO:0006112
|
BP
|
energy reserve metabolic process
|
81
|
2
|
0.0050705
|
1
|
|
GO:0006289
|
BP
|
nucleotide-excision repair
|
106
|
2
|
0.0034318
|
1
|
|
GO:0006518
|
BP
|
peptide metabolic process
|
838
|
3
|
0.0336375
|
1
|
|
GO:0006974
|
BP
|
cellular response to DNA damage stimulus
|
820
|
4
|
0.0095206
|
1
|
|
GO:0007249
|
BP
|
I-kappaB kinase/NF-kappaB signaling
|
269
|
2
|
0.0318732
|
1
|
|
GO:0010467
|
BP
|
gene expression
|
6132
|
10
|
0.0431901
|
1
|
|
GO:0015980
|
BP
|
energy derivation by oxidation of organic compounds
|
251
|
2
|
0.0223538
|
1
|
|
GO:0031334
|
BP
|
positive regulation of protein-containing complex assembly
|
246
|
2
|
0.0395802
|
1
|
|
GO:0033554
|
BP
|
cellular response to stress
|
1994
|
6
|
0.0183496
|
1
|
|
GO:0034599
|
BP
|
cellular response to oxidative stress
|
295
|
2
|
0.0460459
|
1
|
|
GO:0035264
|
BP
|
multicellular organism growth
|
147
|
2
|
0.0208857
|
1
|
|
GO:0043122
|
BP
|
regulation of I-kappaB kinase/NF-kappaB signaling
|
240
|
2
|
0.0262657
|
1
|
|
GO:0043123
|
BP
|
positive regulation of I-kappaB kinase/NF-kappaB signaling
|
177
|
2
|
0.0142479
|
1
|
|
GO:0043170
|
BP
|
macromolecule metabolic process
|
9576
|
14
|
0.0337936
|
1
|
|
GO:0060348
|
BP
|
bone development
|
195
|
2
|
0.0482027
|
1
|
|
GO:0061025
|
BP
|
membrane fusion
|
163
|
2
|
0.0127752
|
1
|
|
GO:0065004
|
BP
|
protein-DNA complex assembly
|
204
|
2
|
0.0122390
|
1
|
|
GO:0071704
|
BP
|
organic substance metabolic process
|
10973
|
15
|
0.0390548
|
1
|
|
GO:0071824
|
BP
|
protein-DNA complex subunit organization
|
243
|
2
|
0.0180409
|
1
|
|
GO:2001020
|
BP
|
regulation of response to DNA damage stimulus
|
215
|
2
|
0.0261995
|
1
|
Cu
Cu = DMP_Cu_cord[[2]]
Cu$chr = paste0('chr', Cu$chr)
Cu = makeGRangesFromDataFrame(Cu, keep.extra.columns = T, start.field = 'start', end.field = 'end')
go_region_metals_Cu <- goregion(Cu, all.cpg=rownames(ComBat.Mvalues.Metals), collection="GO", array.type="450K", plot.bias=TRUE, anno = anno)
table(go_region_metals_Cu$P.DE < 0.05 & go_region_metals_Cu$DE > 1)
# FALSE TRUE
# 22588 22
|
|
ONTOLOGY
|
TERM
|
N
|
DE
|
P.DE
|
FDR
|
|
GO:0005730
|
CC
|
nucleolus
|
1237
|
3
|
0.0045410
|
1
|
|
GO:0006139
|
BP
|
nucleobase-containing compound metabolic process
|
5624
|
5
|
0.0338780
|
1
|
|
GO:0006259
|
BP
|
DNA metabolic process
|
890
|
4
|
0.0002155
|
1
|
|
GO:0006281
|
BP
|
DNA repair
|
531
|
2
|
0.0181810
|
1
|
|
GO:0006304
|
BP
|
DNA modification
|
116
|
2
|
0.0008517
|
1
|
|
GO:0006725
|
BP
|
cellular aromatic compound metabolic process
|
5831
|
5
|
0.0393457
|
1
|
|
GO:0006950
|
BP
|
response to stress
|
3816
|
5
|
0.0062177
|
1
|
|
GO:0006974
|
BP
|
cellular response to DNA damage stimulus
|
820
|
3
|
0.0035479
|
1
|
|
GO:0007596
|
BP
|
blood coagulation
|
319
|
2
|
0.0069770
|
1
|
|
GO:0007599
|
BP
|
hemostasis
|
323
|
2
|
0.0071904
|
1
|
|
GO:0009611
|
BP
|
response to wounding
|
622
|
2
|
0.0267186
|
1
|
|
GO:0016032
|
BP
|
viral process
|
882
|
2
|
0.0470860
|
1
|
|
GO:0033554
|
BP
|
cellular response to stress
|
1994
|
4
|
0.0052096
|
1
|
|
GO:0042060
|
BP
|
wound healing
|
506
|
2
|
0.0176948
|
1
|
|
GO:0046483
|
BP
|
heterocycle metabolic process
|
5790
|
5
|
0.0382336
|
1
|
|
GO:0050817
|
BP
|
coagulation
|
324
|
2
|
0.0070727
|
1
|
|
GO:0050878
|
BP
|
regulation of body fluid levels
|
482
|
2
|
0.0154892
|
1
|
|
GO:0060249
|
BP
|
anatomical structure homeostasis
|
440
|
2
|
0.0133183
|
1
|
|
GO:0090304
|
BP
|
nucleic acid metabolic process
|
5141
|
5
|
0.0226204
|
1
|
|
GO:1901360
|
BP
|
organic cyclic compound metabolic process
|
6056
|
5
|
0.0455929
|
1
|
|
GO:1902494
|
CC
|
catalytic complex
|
1289
|
4
|
0.0010076
|
1
|
|
GO:1990904
|
CC
|
ribonucleoprotein complex
|
655
|
2
|
0.0249823
|
1
|
Hg
Hg = DMP_Hg_cord[[2]]
Hg$chr = paste0('chr', Hg$chr)
Hg = makeGRangesFromDataFrame(Hg, keep.extra.columns = T, start.field = 'start', end.field = 'end')
go_region_metals_Hg <- goregion(Hg, all.cpg=rownames(ComBat.Mvalues.Metals), collection="GO", array.type="450K", plot.bias=TRUE, anno = anno)
table(go_region_metals_Hg$P.DE < 0.05 & go_region_metals_Hg$DE > 1)
# FALSE
# 22610
Mg
Mg = DMP_Mg_cord[[2]]
Mg$chr = paste0('chr', Mg$chr)
Mg = makeGRangesFromDataFrame(Mg, keep.extra.columns = T, start.field = 'start', end.field = 'end')
go_region_metals_Mg <- goregion(Mg, all.cpg=rownames(ComBat.Mvalues.Metals), collection="GO", array.type="450K", plot.bias=TRUE, anno = anno)
table(go_region_metals_Mg$P.DE < 0.05 & go_region_metals_Mg$DE > 1)
# FALSE
# 22610
Mn
Mn = DMP_Mn_cord[[2]]
Mn$chr = paste0('chr', Mn$chr)
Mn = makeGRangesFromDataFrame(Mn, keep.extra.columns = T, start.field = 'start', end.field = 'end')
go_region_metals_Mn <- goregion(Mn, all.cpg=rownames(ComBat.Mvalues.Metals), collection="GO", array.type="450K", plot.bias=TRUE, anno = anno)
table(go_region_metals_Mn$P.DE < 0.05 & go_region_metals_Mn$DE > 1)
# FALSE
# 22610
Se
Se = DMP_Se_cord[[2]]
Se$chr = paste0('chr', Se$chr)
Se = makeGRangesFromDataFrame(Se, keep.extra.columns = T, start.field = 'start', end.field = 'end')
go_region_metals_Se <- goregion(Se, all.cpg=rownames(ComBat.Mvalues.Metals), collection="GO", array.type="450K", plot.bias=TRUE, anno = anno)
table(go_region_metals_Se$P.DE < 0.05 & go_region_metals_Se$DE > 1)
# FALSE TRUE
# 22568 42
|
|
ONTOLOGY
|
TERM
|
N
|
DE
|
P.DE
|
FDR
|
|
GO:0001775
|
BP
|
cell activation
|
1333
|
2
|
0.0056094
|
1.0000000
|
|
GO:0001816
|
BP
|
cytokine production
|
802
|
2
|
0.0016910
|
1.0000000
|
|
GO:0001817
|
BP
|
regulation of cytokine production
|
738
|
2
|
0.0014185
|
1.0000000
|
|
GO:0001819
|
BP
|
positive regulation of cytokine production
|
426
|
2
|
0.0005595
|
1.0000000
|
|
GO:0002376
|
BP
|
immune system process
|
2809
|
2
|
0.0238124
|
1.0000000
|
|
GO:0005576
|
CC
|
extracellular region
|
4105
|
2
|
0.0478340
|
1.0000000
|
|
GO:0005615
|
CC
|
extracellular space
|
3184
|
2
|
0.0291599
|
1.0000000
|
|
GO:0006887
|
BP
|
exocytosis
|
863
|
2
|
0.0023083
|
1.0000000
|
|
GO:0006950
|
BP
|
response to stress
|
3816
|
2
|
0.0437741
|
1.0000000
|
|
GO:0006952
|
BP
|
defense response
|
1595
|
2
|
0.0063818
|
1.0000000
|
|
GO:0006954
|
BP
|
inflammatory response
|
755
|
2
|
0.0014621
|
1.0000000
|
|
GO:0006955
|
BP
|
immune response
|
1875
|
2
|
0.0096718
|
1.0000000
|
|
GO:0008219
|
BP
|
cell death
|
2136
|
2
|
0.0155616
|
1.0000000
|
|
GO:0009605
|
BP
|
response to external stimulus
|
2665
|
2
|
0.0227828
|
1.0000000
|
|
GO:0009607
|
BP
|
response to biotic stimulus
|
1389
|
2
|
0.0050052
|
1.0000000
|
|
GO:0009617
|
BP
|
response to bacterium
|
603
|
2
|
0.0008792
|
1.0000000
|
|
GO:0009893
|
BP
|
positive regulation of metabolic process
|
3642
|
2
|
0.0477884
|
1.0000000
|
|
GO:0010604
|
BP
|
positive regulation of macromolecule metabolic process
|
3358
|
2
|
0.0405217
|
1.0000000
|
|
GO:0010628
|
BP
|
positive regulation of gene expression
|
2178
|
2
|
0.0175673
|
1.0000000
|
|
GO:0012501
|
BP
|
programmed cell death
|
1999
|
2
|
0.0137313
|
1.0000000
|
|
GO:0016192
|
BP
|
vesicle-mediated transport
|
1940
|
2
|
0.0128392
|
1.0000000
|
|
GO:0030141
|
CC
|
secretory granule
|
818
|
2
|
0.0018601
|
1.0000000
|
|
GO:0031410
|
CC
|
cytoplasmic vesicle
|
2282
|
2
|
0.0168427
|
1.0000000
|
|
GO:0031982
|
CC
|
vesicle
|
3791
|
2
|
0.0445436
|
1.0000000
|
|
GO:0031983
|
CC
|
vesicle lumen
|
309
|
2
|
0.0002539
|
0.9962829
|
|
GO:0032940
|
BP
|
secretion by cell
|
1359
|
2
|
0.0061320
|
1.0000000
|
|
GO:0034774
|
CC
|
secretory granule lumen
|
303
|
2
|
0.0002417
|
0.9962829
|
|
GO:0043168
|
MF
|
anion binding
|
2670
|
2
|
0.0253678
|
1.0000000
|
|
GO:0043207
|
BP
|
response to external biotic stimulus
|
1359
|
2
|
0.0047700
|
1.0000000
|
|
GO:0044419
|
BP
|
interspecies interaction between organisms
|
1981
|
2
|
0.0108259
|
1.0000000
|
|
GO:0045055
|
BP
|
regulated exocytosis
|
754
|
2
|
0.0016974
|
1.0000000
|
|
GO:0046903
|
BP
|
secretion
|
1492
|
2
|
0.0075314
|
1.0000000
|
|
GO:0051239
|
BP
|
regulation of multicellular organismal process
|
3220
|
2
|
0.0400224
|
1.0000000
|
|
GO:0051240
|
BP
|
positive regulation of multicellular organismal process
|
1751
|
2
|
0.0124568
|
1.0000000
|
|
GO:0051641
|
BP
|
cellular localization
|
3284
|
2
|
0.0366854
|
1.0000000
|
|
GO:0051649
|
BP
|
establishment of localization in cell
|
2628
|
2
|
0.0228712
|
1.0000000
|
|
GO:0051707
|
BP
|
response to other organism
|
1358
|
2
|
0.0047676
|
1.0000000
|
|
GO:0060205
|
CC
|
cytoplasmic vesicle lumen
|
307
|
2
|
0.0002462
|
0.9962829
|
|
GO:0097708
|
CC
|
intracellular vesicle
|
2286
|
2
|
0.0168876
|
1.0000000
|
|
GO:0098542
|
BP
|
defense response to other organism
|
1026
|
2
|
0.0025281
|
1.0000000
|
|
GO:0099503
|
CC
|
secretory vesicle
|
971
|
2
|
0.0027799
|
1.0000000
|
|
GO:0140352
|
BP
|
export from cell
|
1409
|
2
|
0.0066770
|
1.0000000
|
Zn
Zn = DMP_Zn_cord[[2]]
Zn$chr = paste0('chr', Zn$chr)
Zn = makeGRangesFromDataFrame(Zn, keep.extra.columns = T, start.field = 'start', end.field = 'end')
go_region_metals_Zn <- goregion(Zn, all.cpg=rownames(ComBat.Mvalues.Metals), collection="GO", array.type="450K", plot.bias=TRUE, anno = anno)
table(go_region_metals_Zn$P.DE < 0.05 & go_region_metals_Zn$DE > 1)
# FALSE TRUE
# 22587 23
|
|
ONTOLOGY
|
TERM
|
N
|
DE
|
P.DE
|
FDR
|
|
GO:0000139
|
CC
|
Golgi membrane
|
711
|
2
|
0.0282712
|
1
|
|
GO:0001654
|
BP
|
eye development
|
374
|
2
|
0.0140811
|
1
|
|
GO:0003008
|
BP
|
system process
|
2073
|
3
|
0.0300770
|
1
|
|
GO:0003013
|
BP
|
circulatory system process
|
551
|
2
|
0.0218198
|
1
|
|
GO:0007423
|
BP
|
sensory organ development
|
565
|
2
|
0.0309466
|
1
|
|
GO:0007600
|
BP
|
sensory perception
|
852
|
2
|
0.0176881
|
1
|
|
GO:0007601
|
BP
|
visual perception
|
203
|
2
|
0.0022235
|
1
|
|
GO:0008015
|
BP
|
blood circulation
|
530
|
2
|
0.0200832
|
1
|
|
GO:0030001
|
BP
|
metal ion transport
|
867
|
2
|
0.0496471
|
1
|
|
GO:0034762
|
BP
|
regulation of transmembrane transport
|
545
|
2
|
0.0242811
|
1
|
|
GO:0034765
|
BP
|
regulation of ion transmembrane transport
|
460
|
2
|
0.0187878
|
1
|
|
GO:0035637
|
BP
|
multicellular organismal signaling
|
198
|
2
|
0.0039514
|
1
|
|
GO:0038023
|
MF
|
signaling receptor activity
|
1285
|
2
|
0.0449836
|
1
|
|
GO:0043269
|
BP
|
regulation of ion transport
|
668
|
2
|
0.0346372
|
1
|
|
GO:0044057
|
BP
|
regulation of system process
|
598
|
2
|
0.0298239
|
1
|
|
GO:0048880
|
BP
|
sensory system development
|
384
|
2
|
0.0149061
|
1
|
|
GO:0050877
|
BP
|
nervous system process
|
1306
|
3
|
0.0068245
|
1
|
|
GO:0050953
|
BP
|
sensory perception of light stimulus
|
207
|
2
|
0.0023525
|
1
|
|
GO:0060089
|
MF
|
molecular transducer activity
|
1285
|
2
|
0.0449836
|
1
|
|
GO:0098655
|
BP
|
cation transmembrane transport
|
832
|
2
|
0.0470306
|
1
|
|
GO:0098660
|
BP
|
inorganic ion transmembrane transport
|
816
|
2
|
0.0444199
|
1
|
|
GO:0098662
|
BP
|
inorganic cation transmembrane transport
|
729
|
2
|
0.0356661
|
1
|
|
GO:0150063
|
BP
|
visual system development
|
378
|
2
|
0.0142225
|
1
|